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 -
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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.
KW - time-to-failure (TTF)
KW - insuluation
KW - electrical treeing
KW - insulation TTF
UR - https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=32182
U2 - 10.1109/CEIDP.2014.6995906
DO - 10.1109/CEIDP.2014.6995906
M3 - Paper
T2 - 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena
Y2 - 19 October 2014 through 22 October 2014
ER -