Title :
Remaining useful life prediction based on nonlinear state space model
Author :
Jianmin, Zhao ; Tianle, Feng
Author_Institution :
Mech. Eng. Coll., Shijiazhuang, China
Abstract :
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.
Keywords :
expectation-maximisation algorithm; gears; particle filtering (numerical methods); remaining life assessment; RUL prediction; SSM parameter estimation; expectation maximization algorithm; health degradation estimation; industry asset; nonlinear state space model; particle filtering; remaining useful life prediction; Estimation; prediction; remaining useful life; state space model;
Conference_Titel :
Prognostics and System Health Management Conference (PHM-Shenzhen), 2011
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-7951-1
Electronic_ISBN :
978-1-4244-7949-8
DOI :
10.1109/PHM.2011.5939528
