DocumentCode
1395754
Title
A Birnbaum-Saunders accelerated life model
Author
Owen, W. Jason ; Padgett, William J.
Author_Institution
Dept. of Math. & Stat., New Hampshire Univ., Durham, NH, USA
Volume
49
Issue
2
fYear
2000
fDate
6/1/2000 12:00:00 AM
Firstpage
224
Lastpage
229
Abstract
The 2-parameter family of probability distributions introduced by Birnbaum and Saunders characterizes the fatigue failure of materials subjected to cyclic stresses and strains. It is shown that the methods of accelerated life testing are applicable to the Birnbaum-Saunders distribution for analyzing accelerated lifetime data, and the (inverse) power law model is used due to its justification for describing accelerated fatigue failure in metals. This paper develops the (inverse) power law accelerated form of the Birnbaum-Saunders distribution, and explores the corresponding inference procedures-including parameter estimation techniques and the derivation of the s-expected Fisher information matrix. The model approach in this paper is different from an earlier work, which considered a log-linear form of a model with applications to accelerated life testing. Here, using an example data set, the fitted model is effectively used to estimate lower distribution percentiles and mean failure times for particular values of the acceleration variable. The benefits of having an operable closed form of the Fisher information matrix, which is unique to this article for this model, include interval estimation of model parameters and LCB on percentiles using relatively simple computational procedures
Keywords
failure analysis; fatigue; life testing; parameter estimation; probability; 2-parameter family; Birnbaum-Saunders accelerated life model; Fisher information matrix; accelerated fatigue failure; accelerated lifetime data; cyclic strains; cyclic stresses; distribution percentiles estimation; fatigue failure; inference procedures; inverse power law model; log-linear model; model parameters interval estimation; parameter estimation techniques; probability distributions; s-expected Fisher information matrix; Acceleration; Capacitive sensors; Data analysis; Failure analysis; Fatigue; Life estimation; Life testing; Parameter estimation; Probability distribution; Stress;
fLanguage
English
Journal_Title
Reliability, IEEE Transactions on
Publisher
ieee
ISSN
0018-9529
Type
jour
DOI
10.1109/24.877342
Filename
877342
Link To Document