DocumentCode :
2468025
Title :
An adaptive gamma process based model for residual useful life prediction
Author :
Xu, Wenjia ; Wang, Wenbin
Author_Institution :
Salford Bus. Sch., Univ. of Salford, Salford, UK
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
1
Lastpage :
4
Abstract :
This paper proposes a model to predict the residual useful life of a component by condition monitoring. An adaptive gamma process is used to describe the deteriorating nature of the observed condition indicator but one of the parameters of the gamma model is updated whenever a new observation of the indicator becomes available. The updating is performed by means of a state space model where the parameter is the hidden state variable and the observations are the condition monitoring information. Other unknown model parameters are estimated using the expectation maximization algorithm. We apply the model developed to a case study involving a data set of crack growths and demonstrate the validity of this modeling approach.
Keywords :
condition monitoring; cracks; expectation-maximisation algorithm; gamma distribution; remaining life assessment; adaptive gamma process; condition monitoring; crack growth; expectation maximization algorithm; hidden state variable; residual useful life prediction; state space model; Adaptation models; Estimation; Monitoring; Rail to rail inputs; Welding; condition monitoring; first passage time; gamma process; residual useful life;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and System Health Management (PHM), 2012 IEEE Conference on
Conference_Location :
Beijing
ISSN :
2166-563X
Print_ISBN :
978-1-4577-1909-7
Electronic_ISBN :
2166-563X
Type :
conf
DOI :
10.1109/PHM.2012.6228785
Filename :
6228785
Link To Document :
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