Detection of Mechanical Imbalances of Induction Machines Without Spectral Analysis of Time-Domain Signals

Abstract

Mechanical rotor imbalances and rotor eccentricities are reflected in electric, electromagnetic, and mechanical quantities. Therefore, many surveillance schemes determine the Fourier spectrum of a single line current in order to monitor the motor condition. Mechanical imbalances give rise to two first-order current harmonics. Due to the interaction of the currents and voltages, both these current harmonics are also reflected by a single harmonic component in the frequency spectrum of the electric power. This single component is easier to assess than both the current harmonics. The technique proposed in this contribution evaluates this imbalance-specific modulation of the electric power. The proposed approach does not determine the Fourier spectrum of a time-domain signal, though. First, the imbalance specific oscillation of the electric power is extracted by a bandpass filter. Then, the averaged pattern of this component is determined by means of an angular data clustering technique. In that way, the oscillation of the electric power in the time domain becomes mapped into a discrete waveform in an angular domain. The amplitude of the fundamental harmonic of these discrete data serves as the imbalance indicator of the proposed scheme. This technique, therefore, overcomes small load and slip fluctuations. Measured results of a mechanically unbalanced machine and a case of combined static and dynamic eccentricity are presented.