Abstract:

Condition monitoring vibration data is widely used to assess the health condition of the gearbox. The objective of this paper is to develop a scheme for early fault detection of a gearbox under varying load condition by considering multi-sensor vibration data. Time synchronous averaging (TSA) method is used to reduce the noise and then remove the periodic signals from the data. Several vector auto-regressive (VAR) models are fitted to the historical data obtained in healthy gearbox condition considering different load levels. After testing the independence and multivariate normality of residual data, a multivariate Hotelling’s T-squared control chart is applied to detect the early fault occurrence of a gearbox.