Online cage rotor fault detection using air-gap torque spectra

This paper discusses use of air-gap torque spectra as a means of identifying faults in cage rotors. Being dependent on both stator and rotor currents, the torque is very sensitive to faults in the rotor. Through a comparative study using a detailed machine model and the standard dq model, the paper shows that the characteristic frequencies generated by a particular fault are preserved even if the standard dq model is used for estimation of air-gap torque. This is validated through a practical hardware implementation for online spectrum estimation of air-gap torque using TMS320C31, where several faulted cage rotors were used for study.