Early Detection of Pitting Damage in Gears using Mean Frequency of Scalogram

Abstract

A local gear-tooth defect such as a fatigue crack, pit or chip weakens the tooth and causes transient events when that faulty tooth is in mesh. The magnitude and duration of these events depend mainly upon the severity of the defect and the contact ratio of the gear pair. If the tooth fault severity is small and the contact ratio is high, the resulting transient may not show distinctively in the vibration signal; time-frequency analysis can be used to reveal such events. This paper presents the use of a scalogram and its mean frequency variation for the detection and monitoring of pitting faults in gears. Real gear vibrations are obtained from a test rig utilising a two-stage industrial gearbox. Pits representing differing degrees of fault severity are simulated on a few tooth surfaces. Classical processing schemes in the time and frequency domain are firstly employed to obtain general characteristics of the gear vibration. The continuous wavelet transform is then used to obtain a scalogram and its mean frequency variation. It has been found that the presence of a pitting fault cannot be clearly revealed by the time and frequency domain representations unless the fault severity is high. In contrast, the scalogram (and especially its mean frequency variation) provides early indications of presence and progression of pitting faults in gears even when the fault severity is considerably smaller.