RT Journal Article
T1 Detection of partial discharge sources using UHF sensors and blind signal separation
A1 Boya Lara, Carlos Alan
A1 Robles Muñoz, Guillermo
A1 Parrado Hernández, Emilio
A1 Ruiz Llata, Marta
AB The measurement of the emitted electromagnetic energy in the UHF region of the spectrum allows the detection of partial discharges and, thus, the on-line monitoring of the condition of the insulation of electrical equipment. Unfortunately, determining the affected asset is difficult when there are several simultaneous insulation defects. This paper proposes the use of an independent component analysis (ICA) algorithm to separate the signals coming from different partial discharge (PD) sources. The performance of the algorithm has been tested using UHF signals generated by test objects. The results are validated by two automatic classification techniques: support vector machines and similarity with class mean. Both methods corroborate the suitability of the algorithm to separate the signals emitted by each PD source even when they are generated by the same type of insulation defect.
PB MDPI
SN 1424-3210
YR 2017
FD 2017-11-15
LK https://hdl.handle.net/10016/38617
UL https://hdl.handle.net/10016/38617
LA eng
NO This work has been funded by the Spanish Government through projects TEC2014-52289R and DPI2015-66478-C2-1 (MINECO/FEDER, UE). Carlos Boya acknowledges a doctoral grant sponsored by the National Secretariat for Science, Technology, and Innovation of the Republic of Panama (SENACYT). Tests and measurements have been conducted in the High-voltage Laboratory of the University Carlos III of Madrid.
DS e-Archivo
RD 18 jul. 2024