A Novel Monitoring of Load Level and Broken Bar Fault Severity Applied to Squirrel-Cage Induction Motors Using a Genetic Algorithm

This paper deals with the diagnostic of the signature of rotor broken bars when an induction machine is fed or not by an unbalanced line voltage. These signatures are given by the complex spectrum modulus of line current. In order to make the diagnostic, a genetic algorithm is used to keep the amplitude of all faulty lines. Moreover, a fuzzy logic approach allows us to conclude to the load level operating system and to inform the operator of the rotor fault severity. Several experimental results prove the performance of this method under various load levels and various fault severities. Notwithstanding, this approach requires a steady-state operating condition. The conclusion resulting from this paper is highlighted by experimental results which prove the efficiency of the suggested approach.