Incremental knowledge-based partial discharge diagnosis in oil-filled power transformers

Strachan, Scott and McArthur, S.D.J. and Judd, M.D. and McDonald, J.R. (2005) Incremental knowledge-based partial discharge diagnosis in oil-filled power transformers. In: 13th International Conference on Intelligent Systems Application to Power System (ISAP), 2005-11-06 - 2005-11-10. (https://doi.org/10.1109/ISAP.2005.1599259)

Full text not available in this repository.Request a copy

Abstract

The abstraction of meaningful diagnostic information from raw condition monitoring data in domains where diagnostic expertise and knowledge is limited presents a significant research challenge. This paper proposes a means of abstracting the salient features required to characterize partial discharge (PD) activity detected in oil-filled power transformers. This enables ultra high frequency (UHF) sensor data to be interpreted and translated into a meaningful diagnostic explanation of the observed PD activity. Plant data captured from UHF sensors forms the inputs to a knowledge-based data interpretation system, supporting on-line plant condition assessment and insulation defect diagnosis. The paper describes the functionality of a knowledge-based decision support system, providing engineers with a comprehensive diagnostic explanation of partial discharge activity detected in oil-filled power transformers. The diagnostic output can then be used to advise the engineer in (and potentially automate) the classification and location of partial discharge defect sources

ORCID iDs

Strachan, Scott ORCID logoORCID: https://orcid.org/0000-0002-2690-496X, McArthur, S.D.J. ORCID logoORCID: https://orcid.org/0000-0003-1312-8874, Judd, M.D. and McDonald, J.R.;
CORE (COnnecting REpositories)