Prognostics of transformer paper insulation using statistical particle filtering of on-line data

V. M. Catterson; J. Melone; M. Segovia Garcia

doi:10.1109/MEI.2016.7361101

Prognostics of transformer paper insulation using statistical particle filtering of on-line data

V. M. Catterson, J. Melone, M. Segovia Garcia

Electronic And Electrical Engineering

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

377 Downloads (Pure)

Abstract

Prognostics of transformer remaining life can be achieved through a statistical technique called particle filtering, which gives a more accurate prediction than standard methods by quantifying sources of uncertainty.

Original language	English
Pages (from-to)	28-33
Number of pages	6
Journal	IEEE Electrical Insulation Magazine
Volume	32
Issue number	1
DOIs	https://doi.org/10.1109/MEI.2016.7361101
Publication status	Published - Jan 2016

Keywords

transformer
prognostics
paper insulation
life estimation
condition monitoring

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10.1109/MEI.2016.7361101

Catterson-etal-IEEE-EIM-2016-Prognostics-of-transformer-paper-insulation-using-statistical-particleAccepted author manuscript, 2.76 MB

Cite this

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abstract = "Prognostics of transformer remaining life can be achieved through a statistical technique called particle filtering, which gives a more accurate prediction than standard methods by quantifying sources of uncertainty.",

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KW - condition monitoring

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Prognostics of transformer paper insulation using statistical particle filtering of on-line data

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