Monitoring gear surface degradation using cyclostationarity of acoustic emission. (15th September 2019)

• Record Type: Journal Article
• Authors: Feng, P.; Borghesani, P.; Chang, H.; Smith, W.A.; Randall, R.B.; Peng, Z.
• Is Part Of: Mechanical systems and signal processing. Volume 131(2019)
• Page Start: 199
• Page End: 221
• Publication Date: 2019-09-15
• Subjects: Gear wear -- Acoustic emission -- Generalised Gaussian -- Cyclostationary; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.05.055
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: AE cyclostationary properties are extracted for gear surface degradation monitoring. A new model for AE cyclostationary analysis is proposed. AE-based information is compared with optical microscopy images of the gears. AE cyclic features show strong correlation with different wear mechanisms. Abstract: This paper aims at establishing a correlation between gear wear in spur gears and the statistical properties of AE signals. A generalised Gaussian cyclostationary model is proposed for AE signals measured on gears. This choice is motivated by the characteristics of lubricated contact in spur gears, combining non-stationarity (i.e. cyclostationarity) and non-Gaussianity (i.e. impulsiveness). The former is due to the cyclic kinematics of gear tooth meshing, which leads to a periodicity in the statistics of the AE signal, while the latter is caused by rapid energy release from asperity deformation during gear tooth contact. Two gear wear indicators are defined and estimated based on this assumption (cyclic kurtosis and cyclic scale parameter) and their evolution is monitored against direct measurements of surface degradation in an endurance test. Results show that the proposed indicators are sensitive to monitoring wear phenomena on gear tooth surfaces.