Adaptive Vold–Kalman filtering order tracking

This study proposes and implements an adaptive Vold–Kalman filtering order tracking (VKF_OT) approach to overcome the drawbacks of the original VKF_OT scheme for condition monitoring and diagnosis of rotary machinery. The paper comprises theoretical derivation and numerical implementation. Comparisons of the adaptive VKF_OT scheme to the original are accomplished through processing two synthetic signals composed of close orders and crossing orders, respectively. Parameters such as the weighting factor and the correlation matrix of process noise, which influence tracking performance, are investigated. The adaptive scheme coping with end effects of computation can simultaneously extract multiple order/spectral components, and effectively decouple close and/or crossing orders associated with multi-axial reference rotating speeds. Furthermore, the adaptive OT scheme is realized through Kalman filtering based upon adapted one-step prediction scheme, where a parameter, the weighting factor, is newly introduced into the computation. Thus the technique can be computed on-line and implemented as a real-time processing application.