Gear crack assessment based on cyclic correlation analysis

Gear vibration signals are mainly due to the gear rotating, gear pair meshing and their coupling effects, and are usually modeled as amplitude modulation and frequency modulation (AMFM) processes. The modulation feature of vibration signals is related to the health status of gears. As well, their statistics change periodically with gear rotation, i.e. they are cyclostationary, so cyclostationary analysis is suitable to extract the modulation features of gear vibration signals, so as to detect and assess gear damage. The cyclic auto-correlation function of AMFM signals is deduced, and its properties in cyclic frequency domain are summarized. The ratio between the cyclic autocorrelation slice magnitude at cyclic frequencies of modulating frequency and 0 Hz is a monotonically increasing function of the modulation magnitude, so it is able to indicate the modulation magnitude. Since the modulation magnitude of gear vibration signals is related to localized gear damage degree, the ratio is used to assess the condition of gears. In the analysis of gear crack simulation vibration signals, it shows a monotonically increasing trend with the development of the gear damage. It has potential to early detect incipient damage, to prognosticate severe damage, and to assess gearbox damage.