Nonlinear model for condition monitoring of non-stationary vibration signals in ship driveline application

Abstract

Condition monitoring of mechanical systems is an important topic for industry since it improves machine maintenance and reduce the total associated operational cost. In this sense, vibration analysis is a useful tool for failure prevention in rotating machines, and its main challenge is to perform on-line estimation of dynamic behavior, due to non-stationary operating conditions. To this, estimation of both, amplitude and instantaneous frequency, holding most of process information should be carried out. Nevertheless, approaches for estimating those parameters require to have the shaft speed reference signal, which is not always provided in several industrial applications. In this paper, a novel Order Tracking (OT) scheme of estimation is proposed that is based on the state space model that avoids the shaft speed reference signal. The nonlinear oscillatory model designed as frequency tracker is adapted for estimating the phase and the amplitude of each particular harmonic component. Specifically, nonlinear filtering (namely, the Square-Root Cubature Kalman Filter) is used to estimate the spectral components from the vibration signal. The proposed approach is tested and compared with baseline Vold–Kalman Filtering over four different datasets. The obtained results show that proposed approach is robust and it performs with high accuracy estimation of the order component and the instantaneous frequency under different operating conditions; both allow capturing machine dynamic behavior.