DocumentCode :
1630655
Title :
Component time-to-failure distribution estimation with limited statistical data: A critical survey
Author :
Dent, C.J. ; Gray, J.D.
Author_Institution :
Sch. of Eng. & Comput. Sci., Durham Univ., Durham, UK
fYear :
2011
Firstpage :
1
Lastpage :
8
Abstract :
In many power systems worldwide, a substantial proportion of the network infrastructure was installed in the 1960s, and is thus approaching its design lifetime (typically 40 years). In order to plan replacement programmes, robust means of estimating the distribution of failure dates for classes of component are required. This paper provides a tutorial description of the methods for time-to-failure distribution estimation where not all components in a class have failed, contrasting methods from the reliability literature with a least-squares approach proposed in the power systems literature. The conclusion is that, while on the basis of the limited examples presented here the least-squares approach should not be dismissed definitively, much further work is required before it can be regarded as competitive with standard maximum-likelihood approaches. The accuracy of extrapolation beyond ages at which actual failures have been observed is also discussed; simulation results provide a demonstration of how this can be highly inaccurate unless one has precise knowledge of the correct form of the time-to-failure distribution.
Keywords :
least squares approximations; maximum likelihood estimation; power system parameter estimation; power system reliability; statistical analysis; component time-to-failure distribution estimation; extrapolation; least-squares approach; limited statistical data; power system parameter estimation; power system reliability; standard maximum-likelihood approach; Hazards; Maximum likelihood estimation; Power systems; Probability density function; Reliability; Shape; Life estimation; Power system parameter estimation; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6039574
Filename :
6039574
Link To Document :
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