• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.8
• /
• pp.425-433
• /
• 2002

This research investigates the electromechanical characteristics of a sing1e-phase squirrel cage induction motor due to broken rotor bars and rotor eccentricity. Numerical analysis is performed by solving the nonlinear time-stepping finite element equation coupled with the magnetic field equation, circuit equation and mechanical equation of motion. It shows that the asymmetry of magnetic flux due to the broken rotor bars and rotor eccentricity introduce a change in the stator current, torque, speed, magnetic force and vibration of a rotor at the same time. However, even in the existence of rotor eccentricity, 3 broken rotor bar introduces a dominant change in the magnetic force and rotor displacement, i.e., beating phenomenon in time domain and sideband frequencies in frequency spectra, respectively.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• v.5B no.2
• /
• pp.103-110
• /
• 2005

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1041-1042
• /
• 2007

This paper proposes a new method for detecting broken rotor bars in a squirrel-cage induction motor. The air-gap flux variation analysis was done using search coils inserted in stator slots when broken rotor bar occurs. An accurate modeling and analysis of air-gap flux variation in the induction motor are developed using finite-element (FE) software packages, and measurement of the flux are made using search coils. The simulation was done for the induction motor with 380 [V], 7.5 [kW], 4 Poles, 1,760 [rpm] ratings using the commercial FE analysis tool. The simulation and experiment results can be useful for detecting the broken rotor bar of an induction motor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.802-808
• /
• 2000

This paper characterizes the electromechanical parameters due to the fault of rotor bars in a squirrel cage induction motor. Simulation is performed to investigate how broken rotor bars have effect on them by solving the time-stepping finite element equation coupled with magnetic field equation, circuit equation and mechanical equation of motion. It shows that the asymmetry of magnetic flux due to the broken rotor bar introduces the beating phenomenon in time domain and the sideband frequencies in frequency spectra, respectively, to the stator current, torque, speed, magnetic force and vibration of a rotor. However, vibration of a rotor would be the most effective monitoring parameters to detect the faults of rotor bars.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.3
• /
• pp.342-349
• /
• 2011

This paper presents a study on rotor asymmetry caused by broken bars and its effects on the stator current of an induction machine under an unbalanced supply voltage. The simulation of the induction machine is based on the finite element method. In the early stage of diagnosis, we show new sidebands specific to the partial rupture of the rotor bar. Experimental tests corroborate with the simulation results.

• Journal of Power Electronics
• /
• v.6 no.3
• /
• pp.245-252
• /
• 2006

This paper presents a method based on neural networks to detect the broken rotor bars and end rings of squirrel cage induction motors. At first, detection methods are studied, and then traditional methods of fault detection and dynamic models of induction motors by using winding function model are introduced. In this method, all of the stator slots and rotor bars are considered, thus the performance of the motor in healthy situations or breakage in each part can be checked. The frequency spectrum of current signals is derived by using Fourier transformation and is analyzed in different conditions. In continuation, an analytical discussion and a simple algorithm are presented to detect the fault. This algorithm is based on neural networks. The neural network has been trained by using information of a 1.1 KW induction motor. This system has been tested with a different amount of load torque, and it is capable of working on-line and of recognizing all normal and ill conditions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2006.05a
• /
• pp.475-480
• /
• 2006

In this paper, a new approach for detecting broken rotor bars in a squirrel-cage induction motor is proposed. The air-gap flux variation analysis was done using search coils inserted in stator slots when broken rotor bar occurs. An accurate modeling and analysis of air-gap flux variation in the induction motor are developed using finite-element (FE) software packages, and measurement of the flux are made using search coils. The simulation was done for the induction motor with 380 [V], 5 [HP], 4 Poles, 1,742 [rpm] ratings using the commercial FE analysis tool. The simulation and experiment results can be useful for detecting the broken rotor bar of an induction motor.

• Proceedings of the KIEE Conference
• /
• 1996.07a
• /
• pp.130-132
• /
• 1996

The squirrel cage rotors for induction motors may have several faults such as broken bars, bad spots in the end ring and abnormal skew caused by improper processing. These faults have bad effect on the performance of the induction motor. In this paper, these fault detection method is proposed, then the effects on the performance of the motor is analyzed using FEM.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.65-67
• /
• 1995

The squirrel cage rotors for induction motors may have several faults such as broken bars, bad spots in end ring, abnormal skew caused by improper processing. These faults have bad effect on the performance of the induction motor. This paper proposes the detecting technique of these faults by analyzing the current of the detecting electric magnet, using 2-D finite element method taking account of the rotor movement.

• Proceedings of the KIEE Conference
• /
• 2006.07b
• /
• pp.827-828
• /
• 2006

This paper proposes a new method for detecting broken rotor bars in a squirrel-cage induction motor. The air-gap flux variation analysis was done using search coils inserted in stator slots when broken rotor bar occurs. An accurate modeling and analysis of air-gap flux variation in the induction motor are developed using finite-element(FE) software packages, and measurement of the flux are made using search coils. The simulation was done for the induction motor with 380 [V]. 7.5 [kW], 4 Poles, 1,760 [rpm] ratings using the commercial FE analysis tool. The simulation and experiment results can be useful for detecting the broken rotor bar of an induction motor.