DocumentCode :
2794894
Title :
System reliability assessment using covariate theory
Author :
Wallace, Jon M. ; Mavris, Dimitri N. ; Schrage, Daniel P.
Author_Institution :
Georgia Tech, Atlanta, GA, USA
fYear :
2004
fDate :
26-29 Jan. 2004
Firstpage :
18
Lastpage :
24
Abstract :
A method is demonstrated that utilizes covariate theory to generate a multi-response component failure distribution as a function of pertinent operational parameters. Where traditional covariate theory uses actual measured life data, a modified approach is used herein to utilize life values generated by computer simulation models. The result is a simulation-based component life distribution function in terms of time and covariate parameters for each failure response. A multivariate joint probability covariate model is proposed by combining the covariate marginal failure distributions with the Nataf transformation approach. Evaluation of the joint probability model produced significant improvement in joint probability predictions as compared to the independent series event approach. The proposed methods are executed for a nominal aircraft engine system to demonstrate the assessment of multi-response system reliability driven by a dual mode turbine blade component failure scenario as a function of operational parameters.
Keywords :
covariance analysis; probability; reliability theory; Nataf transformation approach; covariate marginal failure distributions; covariate theory; dual mode turbine blade; joint probability predictions; life distribution function; multiresponse component failure distribution; multiresponse system reliability; multivariate joint probability covariate; nominal aircraft engine system; simulation-based component; system reliability assessment; Computational modeling; Computer simulation; Distribution functions; Hazards; Input variables; Life estimation; Life testing; Predictive models; Reliability; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability and Maintainability, 2004 Annual Symposium - RAMS
Print_ISBN :
0-7803-8215-3
Type :
conf
DOI :
10.1109/RAMS.2004.1285417
Filename :
1285417
Link To Document :
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