H. Hirose

This method uses accelerated life-test data to estimate the mean life at the service stress and the threshold stress below which a failure is unlikely to occur. The relation between stress and mean-life at that stress is assumed to follow an inverse power law that includes a threshold stress. The failure times at a given stress are assumed to follow a Weibull distribution in which the shape parameter varies with the stress. This model extends the well-known Weibull inverse power law model. If only the mean life but not a specific percentile point at a service stress is sought, the maximum likelihood method is useful for parameter estimation. This is a tradeoff in the parametric approach. For adoption of an appropriate probability model, the likelihood ratio test as well as the Akaike Information Criterion are used. Type I right-censored data are considered. Extensions of the method are discussed.

　

Times Cited in Web of Science: 30

Times Cited in Scopus: 11

Times Cited in Google Scholar: 63

Cited in Books: Applied asymptotics: case studies in small-sample statistics 著者: Alessandra R. Brazzale,Anthony Christopher Davison,N. Reid, Cambrifge (2007); Vilijandas Bagdonavicius, Mikhail Nikulin, Accelerated Life Models: Modeling and Statistical Analysis, Chapman & Hall/CRC (2001);
A.C. Davison, D.V. Hinkley, Bootstrap Methods and Their Application, Cambridge (1997)

CiteSeer http://citeseer.nj.nec.com/ ......citation 3, point 3.5

Inspec: 1

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Cited in other journales: 国防科技大学学報, JOURNAL OF NATIONAL UNIVERSITY OF DEFENSE TECHNOL2002 Vol.24 No.2 P.81-84; 兵工学報 ACTA ARMAMENTARII 2004 Vol.25 No.4 P.485-490; R. Boykett1 & P. Livingstone, Using Fatigue History for Preventative Maintenance; N Younis & R. Salman, Degenracy of MIS under the Conditions of Instabilit, Trans. Engineering, Computing and Technollogy, 2005