TY - GEN
T1 - Failure prognosis based on adaptive state space models
AU - Bai, Guangxing
AU - Abdolsamadi, Amirmahyar
AU - Wang, Pingfeng
N1 - Publisher Copyright:
Copyright © 2016 by ASME.
PY - 2016
Y1 - 2016
N2 - This paper presents a generic data-driven failure prognosis method based on adaptive state space models for engineering systems, which integrates adaptive model recognition with a dynamic system model for remaining useful life prediction. The developed approach employs a statistical learning framework for adaptively learning of time-series degradation performance, and then a Bayesian technique for self-updating of data-driven models to adapt the operational or environmental changes. With the developed approach, the prognosis technique can eliminate the dependence to system specific models and be adaptive to system performance changes due to degradation or variation of system operational conditions, thereby yielding accurate remaining useful life predictions. The developed methodology is demonstrated by an engineering case study.
AB - This paper presents a generic data-driven failure prognosis method based on adaptive state space models for engineering systems, which integrates adaptive model recognition with a dynamic system model for remaining useful life prediction. The developed approach employs a statistical learning framework for adaptively learning of time-series degradation performance, and then a Bayesian technique for self-updating of data-driven models to adapt the operational or environmental changes. With the developed approach, the prognosis technique can eliminate the dependence to system specific models and be adaptive to system performance changes due to degradation or variation of system operational conditions, thereby yielding accurate remaining useful life predictions. The developed methodology is demonstrated by an engineering case study.
UR - http://www.scopus.com/inward/record.url?scp=85021646684&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021646684&partnerID=8YFLogxK
U2 - 10.1115/IMECE201666167
DO - 10.1115/IMECE201666167
M3 - Conference contribution
AN - SCOPUS:85021646684
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Advances in Aerospace Technology
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016
Y2 - 11 November 2016 through 17 November 2016
ER -