Research Article Stator Fault Detection in Induction Motors by Autoregressive Modeling Francisco M. Garcia-Guevara, 1 Francisco J. Villalobos-Piña, 1 Ricardo Alvarez-Salas, 2 Eduardo Cabal-Yepez, 3 and Mario A. Gonzalez-Garcia 2 1 Departamento de Ingenier´ ıa Electronica, Instituto Tecnologico de Aguascalientes, Avenida Adolfo Lopez Mateos No. 1801 Oriente, Aguascalientes, AGS, Mexico 2 CIEP, Facultad de Ingenier´ ıa, Universidad Aut´ onoma de San Luis Potos´ ı, Avenida Dr. Manuel Nava No. 8, San Luis Potos´ ı, SLP, Mexico 3 Departamento de Estudios Multidisciplinarios, Division de Ingenier´ ıas Campus Irapuato-Salamanca (DICIS), Universidad de Guanajuato, 38944 Yuriria, GTO, Mexico Correspondence should be addressed to Ricardo Alvarez-Salas; ralvarez@uaslp.mx Received 24 November 2015; Revised 2 March 2016; Accepted 8 March 2016 Academic Editor: Peter Dabnichki Copyright © 2016 Francisco M. Garcia-Guevara et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tis study introduces a novel methodology for early detection of stator short circuit faults in induction motors by using autoregressive (AR) model. Te proposed algorithm is based on instantaneous space phasor (ISP) module of stator currents, which are mapped to - stator-fxed reference frame; then, the module is obtained, and the coefcients 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 diferent-degree fault scenarios during experimentation. 1. Introduction Te fault diagnosis for electrical machines has become far more critical as the population of electric machines has greatly increased in recent years. Te total number of operat- ing electrical machines in the world was around 16.1 billion in 2011, with a growth rate of about 50% in the last fve years [1]. Tree-phase induction motors represent the principal source of movement in the electrical and processing industry [2]. Tis type of motors has an exclusive position in the energy conversion and they are responsible of almost 90% of the electric energy consumed by electric machines. Tree-phase induction motors correspond to nearly 60% of all electric machines [3]. Te success of three-phase induction is due to the low cost, robustness, and high performance in variable speed tasks; this has been achieved through the development of new control laws and more versatile semiconductor devices [4]. However, most control algorithms may not be reliable when a fault condition occurs [1, 2]. Stator short circuit fault diagnosis in three-phase induc- tion motors represents a signifcant percentage of the elec- trical machine defects [5]. In this category there are faults in the stator-winding such as short circuits among turns and the magnetic circuit. In the frst case, the internal asymmetry will cause the circulation of high currents in the portion of the stator-winding afected by the fault, this contributes to the degradation of other portions of the winding, and the remaining time between the onset of fault and the failure depends on various factors such as the initial number of shorted turns, winding confguration, the power and voltage Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2016, Article ID 3409756, 7 pages http://dx.doi.org/10.1155/2016/3409756