论文信息 - 3D analysis of influence of stator winding asymmetry on axial flux

3D analysis of influence of stator winding asymmetry on axial flux

Purpose – The diagnostics of electrical machines is a very important task. The paper seeks to present a study and analysis of stator winding asymmetry in induction motors. The purpose of this paper is presentation of coupling two numerical techniques, a finite element analysis and an artificial neural network, in diagnostics of electrical machines.Design/methodology/approach – A finite element method (FEM) analysis and time‐stepping are applied for the study of IM with stator winding asymmetry. One of the asymmetry symptoms is an axial flux. In order to determine the level of winding asymmetry a generalized regression neural network has been considered. The result of FFT analysis of axial flux and electromagnetic torque was the input vector to artificial neural network. The output vector is the level of asymmetry. The algorithms are tested using a set data obtained from numerical simulation. The emphasis of this structure is on accurate approximation of the value of the stator winding asymmetry.Findings –...

Wojciech Pietrowski

[1] H. Douglas,et al. The detection of interturn stator faults in doubly-fed induction generators , 2005, Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005..

[2] H. Henao,et al. Diagnosis of Broken Bar Fault in Induction Machines Using Discrete Wavelet Transform without Slip Estimation , 2007, 2007 IEEE Industry Applications Annual Meeting.

[3] Humberto Henao,et al. Induction machine fault detection using stray flux EMF measurement and neural network-based decision , 2008 .

[4] Djilali Toumi,et al. Observer-based fault diagnosis and field oriented fault tolerant control of induction motor with stator inter-turn fault , 2012 .

[5] Gérard-André Capolino,et al. Advances in Diagnostic Techniques for Induction Machines , 2008, IEEE Transactions on Industrial Electronics.

[6] Wojciech Pietrowski. Application of Radial Basis Neural Network to diagnostics of induction motor stator faults using axial flux , 2011 .

[7] Mehdi Vakilian,et al. Comparison of transfer functions using estimated rational functions to detect winding mechanical faults in transformers , 2012 .