Detection of Bearing Damage Using Stator Current, and Voltage to Cancel Electrical Noise

This paper investigates the detection of a bearing defect in an asynchronous machine by analysing the electric signals. For this purpose, it is considered that the voltage is imposed and independent of mechanical aspect and that the mechanical defect appears only in the current thanks to the variation of impedance. Wiener filtering is used to extract mechanical information contained in the electrical current; this will then enable the use of statistical indicators such as kurtosis which identify the presence of a defect. Initially, the small fluctuation in electric current around the electric cycle (50 Hz) is reduced in order to reinforce cyclostationarity. Then, a filter between the voltage and current is estimated, using Wiener's technique. Since the voltage is decorrelated of mechanical elements, the residual signal (current − predicted current) contains the mechanical part. This study is corroborated by an envelope analysis of the vibration signal. Experimentation on a faulty outer raceway bearing has shown the excellent performance of the proposed method. This method is easier to implement since the sensors' position does not influence the measure the way it does when using accelerometer sensors. This diagnosis could be embedded into a fed converter. However, it is less sensitive than a direct measure of the defect (accelerometer).

[1]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

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

[3]  C. Tassoni,et al.  Monitoring of induction Machines by maximum covariance method for frequency tracking , 2004, IEEE Transactions on Industry Applications.

[4]  Thomas G. Habetler,et al.  An amplitude Modulation detector for fault diagnosis in rolling element bearings , 2004, IEEE Transactions on Industrial Electronics.

[5]  O.V. Thorsen,et al.  Failure identification and analysis for high voltage induction motors in petrochemical industry , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[6]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

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

[8]  Mohd Jailani Mohd Nor,et al.  Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition , 1998 .

[9]  Robert B. Randall,et al.  On the use of the cyclic power spectrum in rolling element bearings diagnostics , 2005 .

[10]  J. Ilonen,et al.  Diagnosis tool for motor condition monitoring , 2005, IEEE Transactions on Industry Applications.

[11]  C. Hansen,et al.  Estimation of Static Eccentricity Severity in Induction Motors for On-Line Condition Monitoring , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

[12]  P. D. McFadden,et al.  Vibration monitoring of rolling element bearings by the high-frequency resonance technique — a review , 1984 .

[13]  T.G. Habetler,et al.  Motor bearing damage detection using stator current monitoring , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[14]  R. Randall,et al.  OPTIMISATION OF BEARING DIAGNOSTIC TECHNIQUES USING SIMULATED AND ACTUAL BEARING FAULT SIGNALS , 2000 .

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

[16]  Wei Zhou,et al.  Incipient Bearing Fault Detection via Stator Current Noise Cancellation using Wiener Filter , 2007, 2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[17]  F. Guillet,et al.  New applications of the real cepstrum to gear signals, including definition of a robust fault indicator , 2004 .

[18]  Report of Large Motor Reliability Survey of Industrial and Commercial Installations, Part I , 1985, IEEE Transactions on Industry Applications.

[19]  Mohamed El Hachemi Benbouzid A review of induction motors signature analysis as a medium for faults detection , 2000, IEEE Trans. Ind. Electron..

[20]  Antonio Napolitano,et al.  Cyclostationarity: Half a century of research , 2006, Signal Process..

[21]  S. Nandi,et al.  Detection of Stator Faults in Induction Machines Using Residual Saturation Harmonics , 2006, IEEE Transactions on Industry Applications.

[22]  G. Bouleux,et al.  A subspace-based rejection method for detecting bearing fault in asynchronous motor , 2008, 2008 International Conference on Condition Monitoring and Diagnosis.

[23]  A.M. Knight,et al.  Mechanical fault detection in a medium-sized induction motor using stator current monitoring , 2005, IEEE Transactions on Energy Conversion.

[24]  Bertrand Raison,et al.  Signal processing tools for monitoring induction drive , 1999, IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029).

[25]  Robert B. Randall,et al.  THE RELATIONSHIP BETWEEN SPECTRAL CORRELATION AND ENVELOPE ANALYSIS IN THE DIAGNOSTICS OF BEARING FAULTS AND OTHER CYCLOSTATIONARY MACHINE SIGNALS , 2001 .

[26]  A. Ibrahim,et al.  Electrical signals analysis of an asynchronous motor for bearing fault detection , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[27]  François Guillet,et al.  A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor , 2008, IEEE Transactions on Industrial Electronics.

[28]  W. Marsden I and J , 2012 .

[29]  C. Pachaud,et al.  CREST FACTOR AND KURTOSIS CONTRIBUTIONS TO IDENTIFY DEFECTS INDUCING PERIODICAL IMPULSIVE FORCES , 1997 .

[30]  H.A. Toliyat,et al.  Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review , 2005, IEEE Transactions on Energy Conversion.

[31]  Wei Zhou,et al.  Bearing Fault Detection Via Stator Current Noise Cancellation and Statistical Control , 2008, IEEE Transactions on Industrial Electronics.