Diagnosis of eccentricity based on the Hilbert transform of the startup transient current

The Hilbert Transform (HT) can improve the resolution of motor current signature analysis (MCSA), especially at very low slip, because it converts the supply frequency into a continuous component, which can be easily removed to better detect fault harmonics. This paper proposes its application also during speed transients, with two key advantages: first, it allows an easy filtering of the transient current component corresponding to the supply frequency, and, second, the HT allows for the generation of the Hilbert Spectrum, as a replacement of the Fourier Spectrum in the case of non-stationary signals, like those that appear in a transient regime. The performance of the proposed method is compared with other methods as the Discrete Wavelet Transform (DWT), and is validated through simulation with a mathematical model and experimental analysis of a 1.1 kW three-phase squirrel-cage commercial induction motor with eccentricity.

[1]  K. Kodera,et al.  Analysis of time-varying signals with small BT values , 1978 .

[2]  Antonello Monti,et al.  Diagnostic of a Faulty Induction Motor Drive via Wavelet Decomposition , 2007, IEEE Transactions on Instrumentation and Measurement.

[3]  Thomas G. Habetler,et al.  A Survey on Testing and Monitoring Methods for Stator Insulation Systems of Low-Voltage Induction Machines Focusing on Turn Insulation Problems , 2008, IEEE Transactions on Industrial Electronics.

[4]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[5]  R. Puche-Panadero,et al.  Improved Resolution of the MCSA Method Via Hilbert Transform, Enabling the Diagnosis of Rotor Asymmetries at Very Low Slip , 2009, IEEE Transactions on Energy Conversion.

[6]  E. Bedrosian A Product Theorem for Hilbert Transforms , 1963 .

[7]  David G. Dorrell,et al.  The use of finite element methods to improve techniques for the early detection of faults in 3-phase induction motors , 1997 .

[8]  C. Kral,et al.  Detection of mechanical imbalances of induction machines without spectral analysis of time-domain signals , 2004, IEEE Transactions on Industry Applications.

[9]  M. Riera-Guasp,et al.  An Analytical Comparison between DWT and Hilbert-Huang-Based Methods for the Diagnosis of Rotor Asymmetries in Induction Machines , 2007, 2007 IEEE Industry Applications Annual Meeting.

[10]  Guy Clerc,et al.  Classification of Induction Machine Faults by Optimal Time–Frequency Representations , 2008, IEEE Transactions on Industrial Electronics.

[11]  P. Garcia,et al.  Broken Rotor Bar Detection in Line-Fed Induction Machines Using Complex Wavelet Analysis of Startup Transients , 2007, 2007 IEEE Industry Applications Annual Meeting.

[12]  W. T. Thomson,et al.  Current signature analysis to detect induction motor faults , 2001 .

[13]  Alexander G. Parlos,et al.  Induction motor fault diagnosis based on neuropredictors and wavelet signal processing , 2002 .

[14]  A. Nuttall,et al.  On the quadrature approximation to the Hilbert transform of modulated signals , 1966 .

[15]  H.A. Toliyat,et al.  A novel approach for broken rotor bar detection in cage induction motors , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[16]  Antero Arkkio,et al.  DWT analysis of numerical and experimental data for the diagnosis of dynamic eccentricities in induction motors , 2007 .

[17]  Boualem Boashash,et al.  Analytic signal generation-tips and traps , 1994, IEEE Trans. Signal Process..

[18]  D. Vakman,et al.  Computer measuring of frequency stability and the analytic signal , 1994 .

[19]  J.F. Watson,et al.  Improved techniques for rotor fault detection in three-phase induction motors , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[20]  August W. Rihaczek,et al.  Signal energy distribution in time and frequency , 1968, IEEE Trans. Inf. Theory.

[21]  Wenying Huang,et al.  A novel detection method of motor broken rotor bars based on wavelet ridge , 2003 .

[22]  T. S. Radwan,et al.  Real-Time Implementation of Wavelet Packet Transform-Based Diagnosis and Protection of Three-Phase Induction Motors , 2007, IEEE Transactions on Energy Conversion.

[23]  T. G. Habetler,et al.  Sensorless speed measurement of AC machines using analytic wavelet transform , 2002 .

[24]  G. B. Kliman,et al.  Noninvasive detection of broken rotor bars in operating induction motors , 1988 .

[25]  E.D. Mitronikas,et al.  Asynchronous Machine Rotor Fault Diagnosis Technique Using Complex Wavelets , 2008, IEEE Transactions on Energy Conversion.

[26]  Bernard C. Picinbono,et al.  On instantaneous amplitude and phase of signals , 1997, IEEE Trans. Signal Process..

[27]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[28]  David Bonacci,et al.  On-Line Monitoring of Mechanical Faults in Variable-Speed Induction Motor Drives Using the Wigner Distribution , 2008, IEEE Transactions on Industrial Electronics.

[29]  T.G. Habetler,et al.  Nonstationary Motor Fault Detection Using Recent Quadratic Time–Frequency Representations , 2006, IEEE Transactions on Industry Applications.

[30]  Gaëtan Didier,et al.  A new approach to detect broken rotor bars in induction machines by current spectrum analysis , 2007 .

[31]  M. Riera-Guasp,et al.  The use of the wavelet approximation signal as a tool for the diagnosis of rotor bar failures , 2005, 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[32]  Jose A. Antonino-Daviu,et al.  A General Approach for the Transient Detection of Slip-Dependent Fault Components Based on the Discrete Wavelet Transform , 2008, IEEE Transactions on Industrial Electronics.

[33]  G.C. Soukup,et al.  Cause and analysis of stator and rotor failures in 3-phase squirrel cage induction motors , 1991, Conference Record of 1991 Annual Pulp and Paper Industry Technical Conference.

[34]  M. Dalva,et al.  Condition monitoring methods, failure identification and analysis for high voltage motors in petrochemical industry , 1997 .