A non-gaussian continuous state space model for asset degradation
Zhou, Yifan, Ma, Lin, & Mathew, Joseph (2008) A non-gaussian continuous state space model for asset degradation. In Gao, Jinji, Lee, Jay, Ni, Jun, Ma, Lin, & Mathew, Joseph (Eds.) 3rd World Congress on Engineering Asset Management and Intelligent Maintenance Systems Conference, 27th-30th October 2008, Beijing, China.
The degradation model plays an essential role in asset life prediction and condition based maintenance. Various degradation models have been proposed. Within these models, the state space model has the ability to combine degradation data and failure event data. The state space model is also an effective approach to deal with the multiple observations and missing data issues. Using the state space degradation model, the deterioration process of assets is presented by a system state process which can be revealed by a sequence of observations. Current research largely assumes that the underlying system development process is discrete in time or states. Although some models have been developed to consider continuous time and space, these state space models are based on the Wiener process with the Gaussian assumption. This paper proposes a Gamma-based state space degradation model in order to remove the Gaussian assumption. Both condition monitoring observations and failure events are considered in the model so as to improve the accuracy of asset life prediction. A simulation study is carried out to illustrate the application procedure of the proposed model.
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|Item Type:||Conference Paper|
|Keywords:||State space model, Degradation model, Gamma process, Particle smoother|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Mechanical Engineering not elsewhere classified (091399)|
|Divisions:||Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
|Copyright Owner:||Copyright 2008 Springer|
|Copyright Statement:||This is the author-version of the work. Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springerlink.com SpringerLink|
|Deposited On:||13 Nov 2008|
|Last Modified:||29 Feb 2012 13:45|
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