Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis

N Nur Hakimah Binti Ab Aziz, Victoria Catterson, Martin Judd, S.M. Rowland, S. Bahadoorsingh

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

This paper presents a prognostic framework for estimating the time-to-failure (TTF) of insulation samples under electrical treeing stress. The degradation data is taken from electrical treeing experiments on 25 epoxy resin samples. Breakdown occurs in all tests within 2.5 hours. Partial discharge (PD) data from 18 samples are used as training data for prognostic modeling and 7 for model validation. The degradation parameter used in this model is the voltage difference between consecutive PD pulses, which decreases prior to breakdown. Every training sample shows a decreasing exponential trend when plotting the root mean squared (RMS) of the voltage difference for 5 minute batches of data. An average model from the training data is developed to determine the RMS voltage difference during breakdown. This breakdown indicator is verified over three time horizons of 25, 50 and 75 minutes. Results show the best estimation of TTF for 50 minutes of data, with error within quantified bounds. This suggests the framework is a promising approach to estimating insulation TTF.

Conference

Conference2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena
CountryUnited States
CityDes Moines
Period19/10/1422/10/14

Fingerprint

Insulation
Partial discharges
Electric potential
Degradation
Epoxy resins
Experiments

Keywords

  • time-to-failure (TTF)
  • insuluation
  • electrical treeing
  • insulation TTF

Cite this

Nur Hakimah Binti Ab Aziz, N., Catterson, V., Judd, M., Rowland, S. M., & Bahadoorsingh, S. (2014). Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis. Paper presented at 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, Des Moines, United States. https://doi.org/10.1109/CEIDP.2014.6995906
Nur Hakimah Binti Ab Aziz, N ; Catterson, Victoria ; Judd, Martin ; Rowland, S.M. ; Bahadoorsingh, S. / Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis. Paper presented at 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, Des Moines, United States.4 p.
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abstract = "This paper presents a prognostic framework for estimating the time-to-failure (TTF) of insulation samples under electrical treeing stress. The degradation data is taken from electrical treeing experiments on 25 epoxy resin samples. Breakdown occurs in all tests within 2.5 hours. Partial discharge (PD) data from 18 samples are used as training data for prognostic modeling and 7 for model validation. The degradation parameter used in this model is the voltage difference between consecutive PD pulses, which decreases prior to breakdown. Every training sample shows a decreasing exponential trend when plotting the root mean squared (RMS) of the voltage difference for 5 minute batches of data. An average model from the training data is developed to determine the RMS voltage difference during breakdown. This breakdown indicator is verified over three time horizons of 25, 50 and 75 minutes. Results show the best estimation of TTF for 50 minutes of data, with error within quantified bounds. This suggests the framework is a promising approach to estimating insulation TTF.",
keywords = "time-to-failure (TTF) , insuluation, electrical treeing, insulation TTF",
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note = "(c) 2014 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.; 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena ; Conference date: 19-10-2014 Through 22-10-2014",
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Nur Hakimah Binti Ab Aziz, N, Catterson, V, Judd, M, Rowland, SM & Bahadoorsingh, S 2014, 'Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis' Paper presented at 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, Des Moines, United States, 19/10/14 - 22/10/14, . https://doi.org/10.1109/CEIDP.2014.6995906

Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis. / Nur Hakimah Binti Ab Aziz, N; Catterson, Victoria; Judd, Martin; Rowland, S.M.; Bahadoorsingh, S.

2014. Paper presented at 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, Des Moines, United States.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis

AU - Nur Hakimah Binti Ab Aziz, N

AU - Catterson, Victoria

AU - Judd, Martin

AU - Rowland, S.M.

AU - Bahadoorsingh, S.

N1 - (c) 2014 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 - 2014/10

Y1 - 2014/10

N2 - This paper presents a prognostic framework for estimating the time-to-failure (TTF) of insulation samples under electrical treeing stress. The degradation data is taken from electrical treeing experiments on 25 epoxy resin samples. Breakdown occurs in all tests within 2.5 hours. Partial discharge (PD) data from 18 samples are used as training data for prognostic modeling and 7 for model validation. The degradation parameter used in this model is the voltage difference between consecutive PD pulses, which decreases prior to breakdown. Every training sample shows a decreasing exponential trend when plotting the root mean squared (RMS) of the voltage difference for 5 minute batches of data. An average model from the training data is developed to determine the RMS voltage difference during breakdown. This breakdown indicator is verified over three time horizons of 25, 50 and 75 minutes. Results show the best estimation of TTF for 50 minutes of data, with error within quantified bounds. This suggests the framework is a promising approach to estimating insulation TTF.

AB - This paper presents a prognostic framework for estimating the time-to-failure (TTF) of insulation samples under electrical treeing stress. The degradation data is taken from electrical treeing experiments on 25 epoxy resin samples. Breakdown occurs in all tests within 2.5 hours. Partial discharge (PD) data from 18 samples are used as training data for prognostic modeling and 7 for model validation. The degradation parameter used in this model is the voltage difference between consecutive PD pulses, which decreases prior to breakdown. Every training sample shows a decreasing exponential trend when plotting the root mean squared (RMS) of the voltage difference for 5 minute batches of data. An average model from the training data is developed to determine the RMS voltage difference during breakdown. This breakdown indicator is verified over three time horizons of 25, 50 and 75 minutes. Results show the best estimation of TTF for 50 minutes of data, with error within quantified bounds. This suggests the framework is a promising approach to estimating insulation TTF.

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Nur Hakimah Binti Ab Aziz N, Catterson V, Judd M, Rowland SM, Bahadoorsingh S. Prognostic modeling for electrical treeing in solid insulation using pulse sequence analysis. 2014. Paper presented at 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, Des Moines, United States. https://doi.org/10.1109/CEIDP.2014.6995906