With the shift toward electric vehicles, automotive power transmission gears are increasingly required to operate under high-load and high-speed conditions. In particular, friction and wear phenomena occurring at high sliding velocities on gear tooth surfaces, as well as ghost noise induced by surface characteristics, have become important concerns. In general, gear vibration exhibits clear periodicity, and time-synchronous averaging (TSA) is widely employed for vibration analysis. The TSA signal mainly reflects macroscopic information, such as variations in tooth-profile geometry. In contrast, recent studies have focused on analyzing the residual signal obtained by removing the synchronous component from the original signal. In such approaches, the stochastic properties of the residual signal are treated as second-order cyclo-stationarity (CS2), which provides microscopic information related to fine surface asperities. However, second-order cyclo-stationary analysis has been mainly applied to gear tests conducted under low- and medium-speed operating conditions, and its application to high-speed gear tests involving high sliding velocities has been considered difficult due to sensor sensitivity limitations. To clarify the key features and limitations of CS2 analysis under high-speed operating conditions, this study applies second-order cyclo-stationary analysis to gearbox acceleration signals acquired during high-speed gear scuffing tests. In addition, in this study, to extract vibration components in frequency ranges above 10 kHz, where sensor sensitivity significantly decreases, the slope of a CS2 evaluation indicator (ICS2) during the test was introduced. This evaluation was applied to scuffing test results obtained at rotational speeds of 8,000–10,000 rpm using gear pairs with different finishing conditions. As a result, a good correlation was observed between the sliding-induced excitation frequency associated with scuffing scars and the CS2 analysis results. This finding indicates that second-order cyclo-stationary analysis is applicable to high-speed gear vibration for relatively large surface asperities, whereas detecting finer surface features, such as machining marks, requires higher-sensitivity sensors.
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