A feature based method for partial discharge source classification
Lewin, P.L., Petrov, L.A. and Hao, L (2012) A feature based method for partial discharge source classification. In, 2012 IEEE International Symposium on Electrical Insulation (ISEI 2012), San Juan, PR, 10 - 13 Jun 2012. 6pp.
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This paper describes a method for processing PD data captured using a wide bandwidth non-conventional PD sensor such as a radio frequency current transducer (RFCT). The method allows the discrimination between PD signals from multiple PD sources captured by the single sensor. Fundamentally the discrimination is based on the assumption that PD events from the same source will have very similar signatures in terms of time and frequency information whereas there are measurable differences in the signatures of two PD signals from different sources. To visualize this, it is possible to use a dimension reduction technique such that the features of each signal are represented as a single point in three-dimensional space. This process creates clusters of similar signals that can then be analyzed separately as a subset of the original captured data. This approach has been used to analyze PD signal data captured using RFCTs placed around the earth connections of 11 kV three phase belted cables in the UK and Cyprus. Obtained results are analyzed and presented in this paper.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
|Date Deposited:||04 Jul 2012 12:40|
|Last Modified:||27 Mar 2014 20:23|
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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