Nowadays, Induction machines have dominated in the field of electromechanical energy conversion. These machines are often used in critical applications and hostile environments such as corrosive and dusty places. Hence, these undesirable conditions can cause the induction machines to go into unexpected and catastrophic failures. Herein, the broken rotor bar or end-rings and bearing deterioration that causes air gap asymmetric, are rotor faults, which if not detected at its early stages of the failure period, may result in an unserviceable condition of the machine itself, in addition to a likely costly downtime of the whole plant. Therefore use of accurate model and exact fault recognition method in these machines is necessary. Fourier analysis for stator current, torque and rotor speed, acoustic noise, and temperature analysis are several techniques for fault identification. Additionally, neural network method and space vector of rotor magnetic field, based on artificial intelligent approaches and pendulous oscillation of the rotor magnetic field are introduced, respectively. Recently, a new technique based on the analysis of the three-phase stator current envelopes for faults, is presented. So, for analysis of transient and sensitivity and fault diagnosis in induction machines, a detail accreted model is needed. However, the saturation of core, space harmonic distribution and nonsinusoidally winding distributed are neglected in abc quantitative and d-q models method. So, these approaches don’t have accuracy of fault modeling and analysis. For considering distribution rotor bars, coupled magnetic circuit method, abc quantitative based on rotor bar currents are offered. Also for consideration of the stator winding distribution, winding function method is utilized. But in the all of mentioned methods the core saturation, stator and rotor teeth effects, and stator and rotor winding distribution, are not investigated together. Finite element method (FEM) is one of techn
