Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation
We developed particle filter (PF) scheme for dynamical systems with stochastic input. We proposed a bivariate nonstationary growth model to test state estimation methods. We characterized turbine fault symptoms and estimated them by measurable parameters. We proposed a prediction model for turbine degradation using the operating profile. Regularized PF had superior performance than the auxiliary PF in turbine degradation.
state estimation stochastic input turbine degradation dynamical system system identification multivariate particle filter