Analysis techniques for detection of IM broken rotor bars after supply disconnection

Abstract

This paper presents some analysis techniques of the space vector of voltages induced in the stator windings after supply disconnection, to detect broken rotor bars in squirrel-cage induction machines. When the motor is disconnected from the supply no currents flow in the stator windings and the voltages measurable at its terminals are due to flux produced by rotor currents. When the rotor is healthy, the voltages measured at motor terminals are almost sinusoidal because of the symmetry of rotor windings. When there are broken rotor bars, the magnetomotive force generated by rotor windings is distorted, and some particular harmonics, contained in the voltages induced in the stator windings, increase their amplitudes. The diagnostic technique is based on monitoring these voltage harmonics and analyzing the space vector of the voltages induced in the stator windings via MUSIC pseudospectrum and short-time MUSIC (STMUSIC) time-frequency pseudorepresentation. The MUSIC algorithm is based on the eigen analysis of the autocorrelation matrix, and permits us to evidence the principal harmonic frequencies of the signal and decrease the noise influence, thus allowing a better detection of the broken rotor bars. The results obtained using MUSIC and STMUSIC algorithm have been compared experimentally with those obtained by fast Fourier transform (FFT) and short-time FFT, respectively, and two different sized induction motors have been tested, to demonstrate the superiority of the former approach. Differently from most of the diagnostic techniques already proposed in the technical literature, the proposed approach is effective regardless of the load condition of the machine, source characteristics, and iron saturation.