Instantaneous Frequency of the Left Sideband Harmonic During the Start-Up Transient: A New Method for Diagnosis of Broken Bars

In this paper, a new method for detecting the presence of broken rotor bars is presented. The proposed approach is valid for induction machines started at constant frequency and consists of extracting the instantaneous frequency (IF) of the left sideband harmonic (LSH) from the start-up current (LSHst), via the Hilbert transform. It is shown that, in the case of machines with one or several broken bars, the IF of the LSHst exhibits a very characteristic and easy to identify pattern, which is physically justified. This paper also shows that, if the IF of the LSHst is represented against the slip, a universal fault indicator (nondependent neither on the machine characteristics nor on the starting conditions) can be defined. This fault indicator consists of the correlation between the experimental IF of the LSHst and its theoretical evolution. This approach is theoretically introduced and experimentally validated by testing a commercial motor in faulty and healthy conditions, under different operating conditions.

[1]  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.

[2]  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.

[3]  F. Filippetti,et al.  Diagnosis of induction machines in time-varying conditions , 2007, 2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[4]  Dennis Gabor,et al.  Theory of communication , 1946 .

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

[6]  F. Filippetti,et al.  Quantitative evaluation of induction motor broken bars by means of electrical signature analysis , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[7]  A. W. Rihaczek,et al.  Hilbert transforms and the complex representation of real signals , 1966 .

[8]  Ahsan Kareem,et al.  Nonlinear Signal Analysis: Time-Frequency Perspectives , 2007 .

[9]  Chi-Shan Yu,et al.  A new method for power signal harmonic analysis , 2005 .

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

[11]  Gagan Mirchandani,et al.  A frequency-domain method for generation of discrete-time analytic signals , 2006, IEEE Transactions on Signal Processing.

[12]  M. El-Hawary,et al.  Reformulating Three-Phase Power Components Definitions Contained in the IEEE Standard 1459–2000 Using Discrete Wavelet Transform , 2007, IEEE Transactions on Power Delivery.

[13]  D. Casadei,et al.  Monitoring of Induction Machines currents by high frequency resolution analysis , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

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

[15]  C. Hansen,et al.  Detection of Broken Rotor Bar Faults and Effects of Loading in Induction Motors during Rundown , 2007, 2007 IEEE International Electric Machines & Drives Conference.

[16]  Ahsan Kareem,et al.  Efficacy of Hilbert and Wavelet Transforms for Time-Frequency Analysis , 2006 .

[17]  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.

[18]  Damian Giaouris,et al.  Wavelet Denoising for Electric Drives , 2008, IEEE Transactions on Industrial Electronics.

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

[20]  Tadeusz Lobos,et al.  Time–Frequency Analysis of Complex Space Phasor in Power Electronics , 2004, IEEE Transactions on Instrumentation and Measurement.

[21]  Arturo Garcia-Perez,et al.  Automatic Online Diagnosis Algorithm for Broken-Bar Detection on Induction Motors Based on Discrete Wavelet Transform for FPGA Implementation , 2008, IEEE Transactions on Industrial Electronics.

[22]  A. K. Ziarani,et al.  A method of extraction of nonstationary sinusoids , 2004, Signal Process..

[23]  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.

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

[25]  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.

[26]  H. Razik,et al.  Fault detection of broken rotor bars in induction motor using a global fault index , 2006, IEEE Transactions on Industry Applications.

[27]  H. Douglas,et al.  Broken rotor bar detection in induction machines with transient operating speeds , 2005, IEEE Transactions on Energy Conversion.

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

[29]  H. Teager Some observations on oral air flow during phonation , 1980 .

[30]  Mo-Yuen Chow,et al.  Multiple Discriminant Analysis and Neural-Network-Based Monolith and Partition Fault-Detection Schemes for Broken Rotor Bar in Induction Motors , 2006, IEEE Transactions on Industrial Electronics.

[31]  J. Antonino-Daviu,et al.  Application and Optimization of the Discrete Wavelet Transform for the Detection of Broken Rotor Bars in Induction Machines , 2006 .

[32]  Zheng Bao,et al.  Three-band biorthogonal interpolating complex wavelets with stopband suppression via lifting scheme , 2003, IEEE Trans. Signal Process..

[33]  Birsen Yazici,et al.  An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current , 1999 .

[34]  Ahsan Kareem,et al.  Performance of Wavelet Transform and Empirical Mode Decomposition in Extracting Signals Embedded in Noise , 2007 .

[35]  Tommy W. S. Chow,et al.  Induction machine fault diagnostic analysis with wavelet technique , 2004, IEEE Transactions on Industrial Electronics.

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

[37]  P. Tse,et al.  A comparison study of improved Hilbert–Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing , 2005 .

[38]  Tommy W. S. Chow,et al.  Induction machine fault detection using SOM-based RBF neural networks , 2004, IEEE Transactions on Industrial Electronics.

[39]  Bruno Torrésani,et al.  Characterization of signals by the ridges of their wavelet transforms , 1997, IEEE Trans. Signal Process..

[40]  P. Loughlin,et al.  Comments on the interpretation of instantaneous frequency , 1997, IEEE Signal Processing Letters.

[41]  Gérard-André Capolino,et al.  High Frequency Resolution Techniques for Rotor Fault Detection of Induction Machines , 2008, IEEE Transactions on Industrial Electronics.

[42]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. II. A/lgorithms and applications , 1992, Proc. IEEE.

[43]  M. Riera-Guasp,et al.  The Use of the Wavelet Approximation Signal as a Tool for the Diagnosis of Rotor Bar Failures , 2005, IEEE Transactions on Industry Applications.

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

[45]  C. Koley,et al.  Wavelet-aided SVM tool for impulse fault identification in transformers , 2006, IEEE Transactions on Power Delivery.

[46]  F. Filippetti,et al.  AI techniques in induction machines diagnosis including the speed ripple effect , 1996 .

[47]  C. Tassoni,et al.  Thorough Understanding and Experimental Validation of Current Sideband Components in Induction Machines Rotor Monitoring , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[48]  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).

[49]  Fulei Chu,et al.  Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography , 2004 .

[50]  H. Henao,et al.  Diagnosis of Broken Bar Fault in Induction Machines Using Discrete Wavelet Transform without Slip Estimation , 2007, 2007 IEEE Industry Applications Annual Meeting.

[51]  A. Domijan,et al.  Recursive algorithm for real-time measurement of electrical variables in power systems , 2006, IEEE Transactions on Power Delivery.

[52]  Bong-Hwan Kwon,et al.  Online Diagnosis of Induction Motors Using MCSA , 2006, IEEE Transactions on Industrial Electronics.

[53]  David Vakman,et al.  Instantaneous frequency estimation and measurement: a quasi-local method , 2002 .

[54]  W. Rhodes,et al.  Notice of Violation of IEEE Publication PrinciplesUsing Current Signature Analysis Technology to Reliably Detect Cage Winding Defects in Squirrel-Cage Induction Motors , 2007, IEEE Transactions on Industry Applications.

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

[56]  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.

[57]  Wen-Liang Hwang,et al.  Analysis of singularities from modulus maxima of complex wavelets , 2005, IEEE Trans. Inf. Theory.

[58]  M. Tarbouchi,et al.  Speed sensorless estimation of AC induction motors using the fast orthogonal search algorithm , 2006, IEEE Transactions on Energy Conversion.

[59]  S. Mallat A wavelet tour of signal processing , 1998 .

[60]  Cheh Pan Gibbs phenomenon removal and digital filtering directly through the fast Fourier transform , 2001, IEEE Trans. Signal Process..

[61]  Patrick J. Loughlin,et al.  When is instantaneous frequency the average frequency at each time? , 1999, IEEE Signal Processing Letters.

[62]  V. Cizek Discrete Hilbert transform , 1970 .

[63]  A. R. Mohanty,et al.  Fault Detection in a Multistage Gearbox by Demodulation of Motor Current Waveform , 2006, IEEE Transactions on Industrial Electronics.

[64]  I. Culbert,et al.  Using current signature analysis technology to reliably detect cage winding defects in squirrel cage induction motors , 2005 .

[65]  M.M. Morcos,et al.  Automatic diagnosis and location of open-switch fault in brushless DC motor drives using wavelets and neuro-fuzzy systems , 2006, IEEE Transactions on Energy Conversion.

[66]  N.Y. Abed,et al.  Modeling and Characterization of Induction Motor Internal Faults Using Finite-Element and Discrete Wavelet Transforms , 2007, IEEE Transactions on Magnetics.

[67]  H. Henao,et al.  Wavelet Based Instantaneous Power Analysis for Induction Machine Fault Diagnosis , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[68]  K. Selvajyothi,et al.  Extraction of Harmonics Using Composite Observers , 2008, IEEE Transactions on Power Delivery.

[69]  Joachim Holtz,et al.  Sensorless Control of Induction Machines - With or Without Signal Injection? , 2006, IEEE Trans. Ind. Electron..

[70]  Shahin Hedayati Kia,et al.  A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection , 2007, IEEE Transactions on Industrial Electronics.

[71]  M. Riera-Guasp,et al.  Validation of a new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines , 2006, IEEE Transactions on Industry Applications.

[72]  Gabriel Rilling,et al.  One or Two Frequencies? The Empirical Mode Decomposition Answers , 2008, IEEE Transactions on Signal Processing.

[73]  Bruno Torrésani,et al.  Multiridge detection and time-frequency reconstruction , 1999, IEEE Trans. Signal Process..

[74]  J. F. Kaiser,et al.  On a simple algorithm to calculate the 'energy' of a signal , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[75]  A. Walden,et al.  The Hilbert spectrum via wavelet projections , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

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

[77]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[78]  R. Burnett,et al.  The application of modern signal processing techniques for use in rotor fault detection and location within three-phase induction motors , 1996, Signal Process..

[79]  Luis Romeral,et al.  Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition , 2008, IEEE Transactions on Industrial Electronics.

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

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

[82]  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.

[83]  Colin H. Hansen,et al.  Detection of broken rotor bars in induction motor using starting-current analysis and effects of loading , 2006 .

[84]  Alireza Sadeghian,et al.  Current signature analysis of induction motor mechanical faults by wavelet packet decomposition , 2003, IEEE Trans. Ind. Electron..

[85]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

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

[87]  P. P. Vaidyanathan,et al.  Multirate digital filters, filter banks, polyphase networks, and applications: a tutorial , 1990, Proc. IEEE.

[88]  C. Burrus,et al.  Introduction to Wavelets and Wavelet Transforms: A Primer , 1997 .

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

[90]  Richard Kronland-Martinet,et al.  Asymptotic wavelet and Gabor analysis: Extraction of instantaneous frequencies , 1992, IEEE Trans. Inf. Theory.

[91]  Alberto Bellini,et al.  Quantitative Evaluation of Induction Motor Broken Bars By Means of Electric Signals Signatures , 2001 .

[92]  T.G. Habetler,et al.  Detection of Rotor Faults in Brushless DC Motors Operating Under Nonstationary Conditions , 2006, IEEE Transactions on Industry Applications.

[93]  Humberto Henao,et al.  Analytical approach of the stator current frequency harmonics computation for detection of induction machine rotor faults , 2003, 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003..

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

[95]  Mohamed Benbouzid,et al.  Induction motors' faults detection and localization using stator current advanced signal processing techniques , 1999 .

[96]  W.G. Zanardelli,et al.  Identification of Intermittent Electrical and Mechanical Faults in Permanent-Magnet AC Drives Based on Time–Frequency Analysis , 2007, IEEE Transactions on Industry Applications.

[97]  Giovanni Franceschini,et al.  On-field experience with online diagnosis of large induction motors cage failures using MCSA , 2002 .