TY - GEN
T1 - A Copula-based sampling method for data-driven prognostics and health management
AU - Xi, Zhimin
AU - Jing, Rong
AU - Wang, Pingfeng
AU - Hu, Chao
PY - 2013
Y1 - 2013
N2 - This paper develops a Copula-based sampling method for data-driven prognostics and health management (PHM). The principal idea is to first build statistical relationship between failure time and the time realizations at specified degradation levels on the basis of off-line training data sets, then identify possible failure times for on-line testing units based on the constructed statistical model and available on-line testing data. Specifically, three technical components are proposed to implement the methodology. First of all, a generic health index system is proposed to represent the health degradation of engineering systems. Next, a Copula-based modeling is proposed to build statistical relationship between failure time and the time realizations at specified degradation levels. Finally, a sampling approach is proposed to estimate the failure time and remaining useful life (RUL) of on-line testing units. Two case studies, including a bearing system in electric cooling fans and a 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology.
AB - This paper develops a Copula-based sampling method for data-driven prognostics and health management (PHM). The principal idea is to first build statistical relationship between failure time and the time realizations at specified degradation levels on the basis of off-line training data sets, then identify possible failure times for on-line testing units based on the constructed statistical model and available on-line testing data. Specifically, three technical components are proposed to implement the methodology. First of all, a generic health index system is proposed to represent the health degradation of engineering systems. Next, a Copula-based modeling is proposed to build statistical relationship between failure time and the time realizations at specified degradation levels. Finally, a sampling approach is proposed to estimate the failure time and remaining useful life (RUL) of on-line testing units. Two case studies, including a bearing system in electric cooling fans and a 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology.
KW - Copula
KW - Data-driven
KW - Prognostics and health management
KW - Remaining useful life
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U2 - 10.1115/DETC2013-13592
DO - 10.1115/DETC2013-13592
M3 - Conference contribution
AN - SCOPUS:84896951301
SN - 9780791855881
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 39th Design Automation Conference
PB - American Society of Mechanical Engineers
T2 - ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013
Y2 - 4 August 2013 through 7 August 2013
ER -