Search results

This paper presents two modeling methods applied to induction machine study in order to construct a tool for diagnosis purpose. The first method is based on permeance networks using finite element analysis to calculate magnetic equivalent circuit parameters. The second method consists of the elaboration of an electric equivalent circuit obtained from minimal geometrical knowledge on stator and rotor parts of the machine on study. These two methods are presented and their results are compared with respect to the normal and rotor broken bar operation. For this study, a simple structure induction machine with three stator coils and six rotor bars has been investigated. The presented results concern stator currents and electromagnetic torque for the rated speed and the magnitude of the stator current harmonic components have been compared.

The purpose of this paper is to present a study and analysis of insulation failure inter‐turn fault in induction machines (IMs).

A time stepping finite element method (FEM) analysis is performed for the study of IM with inter‐turn fault and determining the machine parameters (self and mutual inductances) after occurring fault. A simple dynamic model for IM with inter‐turn fault is presented. The model parameters are obtained by FEM analysis. An experimental test is also carried out to verify the results.

The behavior of IM is studied under various insulation failure inter‐turn fault conditions and severity using FEM. The paper's results help the machine designers to improve the fault tolerance as well the overall design of the machine drive system. It can also be useful for predict and detection of fault in IM.

Predicting and detection of turn faults in IM are in industry very helpful because it avoids the fully damage of IM and it is more easy to repair the machine. Designing a fault tolerant IM is required in some applications for increasing the reliability.

By using FEM for studying the fault, the machine parameters which are calculated with FEM and the study's results are very precise and accurate because the flux fluctuation after occurring fault has been taken into account. On the other hand, the fault model is very fast, global and accurate. It can be used in model‐based health monitoring systems.