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.
Conference Proceeding: On-line monitoring and diagnosis of broken rotor bars in induction motor[show abstract] [hide abstract]
ABSTRACT: The monitoring and the diagnosis of the defects in induction motors starting from the stator current are very interesting, since it is an accessible and measurable quantity. The spectral analysis of the stator current makes it possible to highlight the characteristic frequencies of the defects but in a wide frequency range depending on half the sampling frequency, making it very difficult to monitor on-line the defects. In order to facilitate the use of the relevant frequencies of the breaking-bar defect we proposed the extraction of the frequency components using two methods, namely, the amplitude and the instantaneous frequency. The theoretical bases of these methods were presented and the results were validated on a test bench with an induction motor of 5.5 kW.Electrical and Electronics Engineering, 2009. ELECO 2009. International Conference on; 12/2009
Article: Determination of the Number of Broken Rotor Bars in Squirrel-Cage Induction Motors Using Wavelet, PCA and Neural Networks[show abstract] [hide abstract]
ABSTRACT: For determination the number of broken rotor bars in squirrel-cage induction motors when these motors are working, this paper presents a new method based on an intelligent processing of the stator transient starting current. In light load condition, distinguishing between safe and faulty rotors is difficult, because the characteristic frequencies of rotor with broken bars are very close to the fundamental component and their amplitudes are small in comparison. To overcome this problem, an advanced technique based on the wavelet transform and artificial neural network is suggested for processing the starting current of induction motors. In order to increase the efficiency of the proposed method, the results of the wavelet analysis, before applying to the neural networks are processed by Principal Component Analysis (PCA). Then the outcome results are supposed as neural network's training and testing data set. The trained neural networks undertake of determining the number of broken rotor bars. The given statistical results, announce the proposed method’s high ability to determine the number of broken rotor bars. The proposed method is independent from loading conditions of machine and it is useable even when the motor is unloaded.International Review of Electrical Engineering 01/2009; 4(2):242-248. · 0.57 Impact Factor
Conference Proceeding: Detection of Broken Rotor Bar Faults and Effects of Loading in Induction Motors during Rundown[show abstract] [hide abstract]
ABSTRACT: The detection of broken rotor bar faults based on the common steady-state Fourier transform technique is known to be dependent on the loading condition and the quality of the supply. This paper attempts to minimise these issues by utilising the induced voltage in the stator windings after supply disconnection. When the supply is disconnected, the stator current rapidly drops to zero and the only source of the stator induced voltage an instant after the supply disconnection is due to currents in the rotor. The rotor currents are sensitive to broken rotor bar faults and directly affect the rundown induced voltage in the stator windings. The performance of two different broken rotor bar detection techniques, based on the Fourier transform and the wavelet transform, are investigated over a wide range of loading conditions.Electric Machines & Drives Conference, 2007. IEMDC '07. IEEE International; 06/2007