|M.Sc Student||Pavel Koulbekov|
|Subject||Condition Monitoring and Diagnosis of Electrical Machines|
|Department||Department of Electrical Engineering||Supervisor||Professor Emeritus Alexandrovitz Abraham|
Early detection of three-phase induction motor faults (pathological states) allows one to prevent failures which cause interruptions of industrial processes and huge economical expenses.
The thesis deals with a development of mathematical models for performance investigation of the three-phase squirrel-cage induction motor in pathological states and its fault diagnostics. The rotor cage is described by an equivalent multi-phase circuit with n rotor loops. In these models it has been taken into account that a stator winding is located in slots and does not possess a sinusoidal distribution.
The mathematical models of the induction motor under different rotor fault cases such as disconnections of adjacent and distant bars, disconnections of adjacent and distant segments of the rotor end-rings, and the model of the motor under inter-turn short- circuit in phase windings have been developed.
Harmonic frequencies of the stator currents have been calculated for all types of the induction motor faults: rotor faults (bars' and end-ring segments' disconnections), inter-turn short-circuit in a stator phase, rotor eccentricities. Expressions for the harmonic frequencies' calculation have been obtained analytically for all pathological states of the induction motor. Knowledge of these harmonic frequencies allows one to perform diagnostics of the motor faults.
Mutual influence of the induction motor under different operating conditions and the shaft-torsional mechanical system is analyzed. The conditions that lead to a critical mechanical state - resonance, are defined.
The simulation results, based on the developed models, of the faulted induction motor equipped with a stiff mechanical system and with shaft-torsional system are shown. A good agreement between the results obtained by the computer simulations and analytical results was demonstrated. As a result, reliable diagnostics of the induction motor faults become possible.