Magnetic Reluctance Method for Dynamical Modeling of Squirrel Cage Induction Machines

Abstract

Nowadays, inductionmachines play important role in electromechanical energy conversion in industry. Thesemachines are often operated in critical conditions where can cause unexpected failures and outages. Generally, stator and bearing faults, broken rotor bar and end-rings, air-gap irregularities are some of the major faults in an induction machine (Al-Shahrani, 2005; Sprooten, 2007) which may be situated the induction machines in out of service (Siddique et al., 2005). Fourier analysis for stator currents (Bellini et al., 2001; Benbouzid, 2000; Jung et al., 2006), torque and rotor speed, acoustic noise and temperature analysis (Siddique et al., 2005) are some classical techniques which introduced for identification and diagnosis of induction machines faults. Additionally, other heuristic methods were proposed to monitor of the induction machines for fault detection. For instance, neural network modelling were applied to monitor an induction machine for fault detection (Su & Chong, 2007). Also, space vector of rotor magnetic field (Mirafzal & Demerdash, 2004) based on artificial intelligent approaches and pendulous oscillation of the rotor magnetic field were proposed. Recently, a new technique based on the analysis of three-phase stator current envelopes was presented (Mirafzalet & Demerdash, 2008). In all monitoring and fault detection techniques, we need to tune up the monitoring systems based on response of induction machines for proper operations. However, experimental set up for testing any arbitrary fault conditions are not practical. Thus, an accuracy dynamic and steady state models of induction machines are very important for this propose. Also, for dynamical modelling of induction machines, space harmonic distribution, core saturation and loss are often neglected in abc quantitative and two-axis methods (Krause et al., 1995). Thus, these approaches do not have an efficient accuracy for modelling of induction machines in asymmetrical and non-linear conditions. For considering distribution rotor bars, coupled magnetic circuit method (Munoz & Lipo, 1999), abc quantitative based on rotor bar currents (Alemi & Nazarzadeh, 1996) can be utilized. Furthermore, winding function method may be used to include the stator winding distribution effect in the air gap flux (Luos et al., 1995). However, in all mentioned methods, the core saturation, stator and rotor teeth effects and distributions of the rotor and stator windings can not be investigated, simultaneously. Also, Finite Element Method (FEM) is a professional technique for analysis of any electromagnetic systems, which needs to magnetic and geometry details of the systems (Faiz 3