abstract

• This study introduces a novel methodology for early detection of stator short circuit faults in induction motors by using autoregressive (AR) model. The proposed algorithm is based on instantaneous space phasor (ISP) module of stator currents, which are mapped to α - β stator-fixed reference frame; then, the module is obtained, and the coefficients of the AR model for such module are estimated and evaluated by order selection criterion, which is used as fault signature. For comparative purposes, a spectral analysis of the ISP module by Discrete Fourier Transform (DFT) is performed; a comparison of both methodologies is obtained. To demonstrate the suitability of the proposed methodology for detecting and quantifying incipient short circuit stator faults, an induction motor was altered to induce different-degree fault scenarios during experimentation. © 2016 Francisco M. Garcia-Guevara et al.

authors

• Cabal-Yepez E.
• Garcia-Guevara F.M.
• Gonzalez-Garcia M.A.
• Villalobos-Piña F.J.
• Álvarez Salas Ricardo

publication date

• 2016-01-01

published in

• Mathematical Problems in Engineering  Journal

keywords

• Discrete Fourier transforms; Fault detection; Spectrum analysis; Stators; Auto regressive models; Fault signature; Novel methodology; Order selection; Reference frame; Short-circuit fault; Stator currents; Stator fault detection; Induction motors

Digital Object Identifier (DOI)

• 10.1155/2016/3409756

start page

end page

volume

• 2016