High Frequency Resolution Techniques for Rotor Fault Detection of Induction Machines

Motor current signature analysis (MCSA) is the reference method for diagnosis of medium-large machines in industrial applications. However MCSA is still an open research topic, as some signatures may be created by different phenomena, and it may become sensitive to load and inertia variations, and with respect to an oscillating load torque,though suitable data normalization can be applied.Recently the topic of diagnostic techniques for drives and low-medium size machines isbecoming attractive, as the procedure can be embedded in the drive at no additionalcost but the dedicated firmware, provided that a suitable computational cost is required.In this paper, statistical time domain techniques are used totrack grid frequency and machine slip that feature either a lowercomputational cost or a higher accuracy than traditional discreteFourier transform techniques. Then, the knowledge of both grid frequency and machine slip are used to tune theparameters of the zoom-FFT algorithm that either increasesthe frequency resolution keeping constant the computational costor reduces the computational cost keeping constant the frequencyresolution. The proposed technique is validated for rotorfaults.