Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item DQ modeling of induction motor for virtual flux measurement(2010) Sushma, P.; Rajalakshmi Samaga, R.; Vittal, K.P.Three phase induction motors are continuing to remain as work horses in industrial applications. The accurate behavioral modeling of induction motor helps in designing controller for the machine and also useful in detection of faults in machines. Almost all faults in the induction motor affect the flux in the air gap. These fluxes can be measured virtually using dq model of induction motor by feeding voltage and current values extracted in real time and stored. In this paper, DQ model is developed in stator reference frame using MATLAB-SIMULINK platform and a data acquisition system supported with LabVIEW is used to obtain motor terminal voltage and current signals which are useful in estimation of flux in an actual machine. ©2010 IEEE.Item Investigation into effect of mixed air gap eccentricity on dq components of currents in induction motor(2011) Rajalakshmi Samaga, R.; Vittal, K.P.dq components of currents are extensively used in the controller applications of industrial drives as they are dc quantities. In this paper, it is shown that these components will no longer remain as dc quantities, if they are extracted from the induction motor suffering from mixed air gap eccentricity. A dynamic model of an induction motor suffering from mixed air gap eccentricity is developed and simulated to show the presence of eccentricity characteristic harmonics in dq components of the stator currents in synchronous reference frame. In this paper, it is also shown that the frequency analysis of dq currents helps in the detection of air gap non uniformity in the machine. The results obtained by modeling and simulation are also validated experimentally. © 2011 IEEE.Item Air gap mixed eccentricity severity detection in an induction motor(2011) Rajalakshmi Samaga, R.; Vittal, K.P.Non invasive fault detection unit for an induction motor has become an integral part of industrial drives. As the current is the primary quantity to get affected by the non uniform air gap flux, Motor Current Signature Analysis is preferred as compared to vibration analysis for mixed eccentricity fault detection in an induction motor. In this paper, Power Spectral Density analysis is performed on the stator current data samples obtained from modeling and simulation of the induction motor. An Eccentricity Severity Factor is defined and is shown that this factor increases with increase of air gap eccentricity in the machine. Hence it can be used as a measure to assess the degree of eccentricity in the machine. © 2011 IEEE.