Adaptive modelling of transient vibration signals

Abstract

Conventional vibration signal processing techniques are most suitable for stationary processes. However, most mechanical faults in machinery reveal themselves through transient events in vibration signals. Time-series modelling, including autoregressive moving average (ARMA) modelling and autoregressive (AR) modelling, is an efficient approach for transient signal analysis. Based on the adaptive prediction technique, this paper applies the principle of the adaptive line enhancer (ALE) to the modelling of transient vibration signals. The time-series models, adaptive algorithms and the rational time–frequency transfer function are investigated in the paper. Simulation and experimental studies with different time–frequency–amplitude distributions and transient vibration responses are described. The results show that the adaptive modelling method can trace the time–frequency signal and extract dynamic features such as time–frequency distributions and time–amplitude distributions from sample signals. Given the simple programming and potentially easy implementation in on-line applications, this method should have application in machine monitoring and fault diagnosis.