A number of gearbox failures can be attributed to lubricant related problems. One measure of the condition of gearbox oil is its viscosity. In electrically powered systems, motor current signal analysis allows online estimation of the viscosity of gearbox oil without requiring additional sensors. Previous work on this problem entailed monitoring the power (and change in power) of sidebands of the shaft frequency in the induction motor current spectrum. Sideband frequencies in the current spectrum can however be influenced by other potential problems in the electromechanical system ranging from bearing faults to gearbox teeth damage. Changes in the lubricant viscosity result in changes in the mechanical and thermal losses in the system. These small deviations in the mechanical and thermal losses in the system become visible in the ratio of the electrical energy demanded by the induction motor to the kinetic energy of the rotating mechanical parts. Speed and load invariance can be ensured by normalizing the measured energy ratio with lookup table values obtained when the system attained thermal equilibrium. Speed or load perturbations in the system give rise to small deviations in the normalized energy ratio curve. The distributions of these deviations are significantly different (in a statistical sense) for different oil viscosity values.
|Title of host publication||1st World Congress on Condition Monitoring|
|Subtitle of host publication||(WCCM 2017)|
|Publisher||British Institute of Non-Destructive Testing|
|Number of pages||12|
|Publication status||Published - 2017|
|Event||1st World Congress on Condition Monitoring - ILEC Conference Centre, London, United Kingdom|
Duration: 13 Jun 2017 → 16 Jun 2017
http://www.bindt.org/events/PastEvents/WCCM-2017/ (Link to Conference Website)
|Conference||1st World Congress on Condition Monitoring|
|Abbreviated title||WCCM 2017|
|Period||13/06/17 → 16/06/17|
Van Vuuren, P. A., Xu, Y., Gu, F., & Ball, A. D. (2017). Monitoring gearbox oil viscosity by means of motor current signal analysis. In 1st World Congress on Condition Monitoring: (WCCM 2017) (Vol. 1, pp. 170-181). British Institute of Non-Destructive Testing.