Analysis of Partial Discharge Features as Prognostic Indicators of Electrical Treeing

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

doi:10.1109/TDEI.2016.005957

Analysis of Partial Discharge Features as Prognostic Indicators of Electrical Treeing

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

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

116 Downloads (Pure)

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
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 - 7 Mar 2017

Access to Document

10.1109/TDEI.2016.005957

Aziz Catterson Rowland Bahadoorsingh TDEI as acceptedAccepted author manuscript, 3.56 MB

Cite this

@article{e37ad2c43a0e4d50a8a5784ce3be6371,

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. ",

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

year = "2017",

month = mar,

day = "7",

doi = "10.1109/TDEI.2016.005957",

language = "English",

volume = "24",

journal = "IEEE Transactions on Dielectrics and Electrical Insulation",

issn = "1070-9878",

publisher = "IEEE",

number = "1",

}

TY - JOUR

T1 - Analysis of Partial Discharge Features as Prognostic Indicators of Electrical Treeing

AU - Ab Aziz , N. H.

AU - Catterson , V. M.

AU - Rowland, Simon

AU - Bahadoorsingh , S.

PY - 2017/3/7

Y1 - 2017/3/7

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.

U2 - 10.1109/TDEI.2016.005957

DO - 10.1109/TDEI.2016.005957

M3 - Article

SN - 1070-9878

VL - 24

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

Access to Document

Fingerprint

Cite this