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Activity Number:
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516
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #303794 |
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Title:
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Prediction of Remaining Life of Power Transformers Based on Left-Truncated and Right-Censored Lifetime Data
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Author(s):
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Yili Hong*+ and William Q. Meeker and James D. McCalley
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Companies:
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Iowa State University and Iowa State University and Iowa State University
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Address:
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Snedecor Hall, Ames, IA, 50011,
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Keywords:
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Maximum likelihood ; random weighted bootstrap ; reliability ; regression analysis ; transformer maintenance
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Abstract:
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Prediction of the remaining life of high-voltage power transformers is an important issue for energy companies because of the need for planning maintenance and capital expenditures. Lifetime data for such transformers are complicated because transformer lifetimes can extend over many decades and transformer designs and manufacturing practices have evolved. We were asked to develop predictions for the lifetimes of an energy company's fleet of transformers. The data are left truncated and right censored. We use a parametric lifetime model to describe the lifetime distribution of individual transformers. We develop a statistical procedure, based on age-adjusted life distributions, for computing a prediction interval (PI) for remaining life for those still in service. We then extend these ideas to provide predictions and PIs for the cumulative number of failures for the overall population.
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