Condition Monitoring of Helical Gears Using Acoustic Emission (AE) Technology

摘要

Techniques such as vibration monitoring, thermal analysis and oil analysis are wellestablished as means to have been used to improve reliability of gearboxes and extendtime-to-failure. In this area Acoustic Emission (AE) technology is still in its infancy butthe attention shown by researchers towards this method has increased dramaticallybecause several studies have shown the AE offers the important advantage of improvedsensitivity over more conventional monitoring tools for the early detection andprediction of gear failure.Helical gear lubrication is critically important for maintaining the integrity of operatinggears and the oil also prevents asperity contact at the gear mesh thereby protecting thegears from a deterioration process and surface failures. In gear systems, there are threetypes of lubrication regimes: Dry Running, Boundary Lubrication (BL), HydrodynamicLubrication (HL) and Elastohydro-dynamic Lubrication (EHL). The last regime isassociated with the normal operating running condition of gears.Acoustic emissions were acquired from gears and analysed for different lubricationregimes (dry, BL, HL and EHL regimes at different temperatures), and correspondingspecific film thicknesses (λ) levels. The results showed an inverse relationship betweenAE signal levels and specific film thickness (λ) of the oil. This relation was used todetermine the lubrication regime from the measured AE signals. For instance, dryrunning had the highest AE levels which were attributed to the metal-to-metal contact ofthe gear mesh. The BL regime had relatively high AE levels which also attributed to thelevel of asperity contact is greater than the oil film thickness. The HL regime wascharacterized by the lowest AE levels due to the lubricant oil completely separating theteeth during gear meshing. Finally, the EHL regime showed intermediate AE levelscompared to the BL and HL regimes because the oil film was less than for the HLregime but greater than for the BL regime.It is shown that the application of advanced signal processing methods is necessary formonitoring helical gears; Kurtosis and Spectral Kurtosis were used to investigate theAE signatures and found to be effective in de-noising (spectral kurtosis) acquiredsignals. Acoustic Emission proved to be a powerful tool to detect the oil regime for bothdefective and non-defective conditions.It is concluded that the experimental findings of this research programme will providethe foundations for significant advancement in the application of AE for thedetermining the lubrication regime present within a helical gearbox and for the detectionof developing gear faults. This should give a new impetus in the field of maintenanceand prevention of human and material catastrophes.Several papers presenting the findings of this research have been published ininternational journals and given at conferences.