Monitoring tooth profile faults in epicyclic gearboxes using synchronously averaged motor currents: Mathematical modeling and experimental validation

Abstract Time-varying transmission paths and inaccessibility can increase the difficulty in both acquiring and processing vibration signals for the purpose of monitoring epicyclic gearboxes. Recent work has shown that the synchronous signal averaging approach may be applied to measured motor currents in order to diagnose tooth faults in parallel shaft gearboxes. In this paper we further develop the approach, so that it may also be applied to monitor tooth faults in epicyclic gearboxes. A low-degree-of-freedom model of an epicyclic gearbox which incorporates the possibility of simulating tooth faults, as well as any subsequent tooth contact loss due to these faults, is introduced. By combining this model with a simple space-phasor model of an induction motor it is possible to show that, in theory, tooth faults in epicyclic gearboxes may be identified from motor currents. Applying the synchronous averaging approach to experimentally recorded motor currents and angular displacements recorded from a shaft mounted encoder, validate this finding. Comparison between experiments and theory highlight the influence of operating conditions, backlash and shaft couplings on the transient response excited in the currents by the tooth fault. The results obtained suggest that the method may be a viable alternative or complement to more traditional methods for monitoring gearboxes. However, general observations also indicate that further investigations into the sensitivity and robustness of the method would be beneficial.

[1]  James R. Ottewill,et al.  Condition monitoring of gearboxes using synchronously averaged electric motor signals , 2013 .

[2]  Jawad Faiz,et al.  Planetary Gearbox Torsional Vibration Effects on Wound-Rotor Induction Generator Electrical Signatures , 2015, IEEE Transactions on Industry Applications.

[3]  R. C. Kryter,et al.  Condition monitoring of machinery using motor current signature analysis , 1989 .

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

[5]  Ming J. Zuo,et al.  Fault diagnosis of planetary gearboxes via torsional vibration signal analysis , 2013 .

[6]  R. G. Munro,et al.  Dynamic Behaviour of Spur Gears , 1963 .

[7]  Chandana Jayampathi Gajanayake,et al.  Stator Current Analysis From Electrical Machines Using Resonance Residual Technique to Detect Faults in Planetary Gearboxes , 2015, IEEE Transactions on Industrial Electronics.

[8]  Robert G. Parker,et al.  Nonlinear Dynamics of Planetary Gears Using Analytical and Finite Element Models , 2007 .

[9]  Amiya R Mohanty,et al.  Monitoring gear vibrations through motor current signature analysis and wavelet transform , 2006 .

[10]  Robert G. Parker,et al.  SENSITIVITY OF PLANETARY GEAR NATURAL FREQUENCIES AND VIBRATION MODES TO MODEL PARAMETERS , 1999 .

[11]  W. T. Thomson,et al.  Motor Current Signature Analysis To Detect Faults In Induction Motor Drives - Fundamentals, Data Interpretation, And Industrial Case Histories. , 2003 .

[12]  Robert B. Randall,et al.  Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications , 2011 .

[13]  Robert G. Parker,et al.  Analytical Characterization of the Unique Properties of Planetary Gear Free Vibration , 1999 .

[14]  Fakher Chaari,et al.  Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis , 2010 .

[15]  Peter Vas,et al.  Sensorless vector and direct torque control , 1998 .

[16]  J. D. Smith,et al.  Gear Noise and Vibration , 1999 .

[17]  Long Wu.  Separating Load Torque Oscillation and Rotor Faults in Stator Current Based-Induction Motor Condition Monitoring , 2006 .

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

[19]  David G. Lewicki,et al.  Planetary Gearbox Fault Detection Using Vibration Separation Techniques , 2011 .

[20]  Amiya R Mohanty,et al.  Multistage gearbox condition monitoring using motor current signature analysis and Kolmogorov–Smirnov test , 2006 .

[21]  P. D. McFadden,et al.  A technique for calculating the time domain averages of the vibration of the individual planet gears and the sun gear in an epicyclic gearbox , 1991 .

[22]  Shahin Hedayati Kia,et al.  Gear tooth surface damage fault detection using induction machine electrical signature analysis , 2013, 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED).

[23]  Yaguo Lei,et al.  Fault detection of planetary gearboxes using new diagnostic parameters , 2012 .

[24]  Ahmet Kahraman,et al.  Natural Modes of Planetary Gear Trains , 1994 .

[25]  Dong Han,et al.  Planetary gearbox fault diagnosis using an adaptive stochastic resonance method , 2013 .

[26]  H. Henao,et al.  Trends in gear fault detection using electrical signature analysis in induction machine-based systems , 2015, 2015 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD).

[27]  Liu Hong,et al.  A time domain approach to diagnose gearbox fault based on measured vibration signals , 2014 .

[28]  Robert G. Parker,et al.  PLANETARY GEAR PARAMETRIC INSTABILITY CAUSED BY MESH STIFFNESS VARIATION , 2002 .

[29]  Yaguo Lei,et al.  Condition monitoring and fault diagnosis of planetary gearboxes: A review , 2014 .

[30]  Amiya R Mohanty,et al.  Vibration and current transient monitoring for gearbox fault detection using multiresolution Fourier transform , 2008 .