Analysis of partial discharge features as prognostic indicators of electrical treeing

N.H. Aziz; V. M. Catterson; S. M. Rowland; S. Bahadoorsingh

doi:10.1109/TDEI.2016.005957

Analysis of partial discharge features as prognostic indicators of electrical treeing

N.H. Aziz, V. M. Catterson, S. M. Rowland, S. Bahadoorsingh

Electronic And Electrical Engineering

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

16 Citations (Scopus)

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Abstract

The aim of this paper is to identify promising indicators for prognosis of electrical treeing. Both phase-resolved partial discharge analysis (PRPDA) and pulse sequence analysis (PSA) are utilized. The prognostic properties of the features are evaluated in terms of monotonicity, prognosability, and trendability. The investigation reveals that PSA has a higher prognostic suitability index than PRPDA. An exponential fit is applied to the feature with the highest suitability index, in order to demonstrate its use for prognostic modeling and prediction of time until breakdown.

Original language	English
Pages (from-to)	129-136
Number of pages	9
Journal	IEEE Transactions on Dielectrics and Electrical Insulation
Volume	24
Issue number	1
DOIs	https://doi.org/10.1109/TDEI.2016.005957
Publication status	Published - 28 Feb 2017

Keywords

electrical treeing
partial discharge
pulse sequence analysis
phase-resolved partial discharge analysis
prognostic
lifetime model
curve fitting

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Ab-Aziz-etal-TDEI-2016-partial-discharge-features-as-prognostic-indidicators-of-electrical-treeingAccepted author manuscript, 5.89 MB

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title = "Analysis of partial discharge features as prognostic indicators of electrical treeing",

abstract = "The aim of this paper is to identify promising indicators for prognosis of electrical treeing. Both phase-resolved partial discharge analysis (PRPDA) and pulse sequence analysis (PSA) are utilized. The prognostic properties of the features are evaluated in terms of monotonicity, prognosability, and trendability. The investigation reveals that PSA has a higher prognostic suitability index than PRPDA. An exponential fit is applied to the feature with the highest suitability index, in order to demonstrate its use for prognostic modeling and prediction of time until breakdown.",

keywords = "electrical treeing, partial discharge, pulse sequence analysis, phase-resolved partial discharge analysis, prognostic, lifetime model, curve fitting",

author = "N.H. Aziz and Catterson, {V. M.} and Rowland, {S. M.} and S. Bahadoorsingh",

note = "(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works",

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AU - Aziz, N.H.

AU - Catterson, V. M.

AU - Rowland, S. M.

AU - Bahadoorsingh, S.

N1 - (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

PY - 2017/2/28

Y1 - 2017/2/28

N2 - The aim of this paper is to identify promising indicators for prognosis of electrical treeing. Both phase-resolved partial discharge analysis (PRPDA) and pulse sequence analysis (PSA) are utilized. The prognostic properties of the features are evaluated in terms of monotonicity, prognosability, and trendability. The investigation reveals that PSA has a higher prognostic suitability index than PRPDA. An exponential fit is applied to the feature with the highest suitability index, in order to demonstrate its use for prognostic modeling and prediction of time until breakdown.

AB - The aim of this paper is to identify promising indicators for prognosis of electrical treeing. Both phase-resolved partial discharge analysis (PRPDA) and pulse sequence analysis (PSA) are utilized. The prognostic properties of the features are evaluated in terms of monotonicity, prognosability, and trendability. The investigation reveals that PSA has a higher prognostic suitability index than PRPDA. An exponential fit is applied to the feature with the highest suitability index, in order to demonstrate its use for prognostic modeling and prediction of time until breakdown.

KW - electrical treeing

KW - partial discharge

KW - pulse sequence analysis

KW - phase-resolved partial discharge analysis

KW - prognostic

KW - lifetime model

KW - curve fitting

U2 - 10.1109/TDEI.2016.005957

DO - 10.1109/TDEI.2016.005957

M3 - Article

SN - 1070-9878

VL - 24

SP - 129

EP - 136

JO - IEEE Transactions on Dielectrics and Electrical Insulation

JF - IEEE Transactions on Dielectrics and Electrical Insulation

IS - 1

ER -

Analysis of partial discharge features as prognostic indicators of electrical treeing

Abstract

Keywords

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