Remaining useful life prediction based on nonlinear state space model

This paper proposes a nonlinear state space model (SSM) to estimate the health degradation and predict the remaining useful life(RUL) of industry asset. Expectation Maximization (EM) algorithm and particle filtering (PF) are introduced to estimate SSM parameters. A case study is utilized to predict RUL of industry asset.