Dynamic signal interpretation of rotary machines using adaptive order tracking

This paper proposes and implements an adaptive Vold-Kalman filtering order tracking (VKF_OT) approach to overcome the deficiencies of the original VKF_OT scheme for condition monitoring and diagnosis of rotary machinery. This article comprises theoretical derivation, numerical implementation and experimental validation. Comparisons of the adaptive scheme to the original are accomplished through processing a synthetic signal composed of close order components. Parameters such as the weighting factor and the correlation matrix of process noise, which influences tracking performance, are investigated in the study. The adaptive OT scheme based on the Kalman filter can be computed on-line and implemented as a real-time processing application. This paper also illustrates experimental validation through the separation of two close orders arising from a transmission test bench.