Boya Lara, Carlos AlanRobles Muñoz, GuillermoParrado Hernández, EmilioRuiz Llata, Marta2023-10-172023-10-172017-11-15Boya, C., Robles, G., Parrado-Hernández, E., & Ruiz-Llata, M. (2017). Detection of partial discharge sources using UHF sensors and blind signal separation. Sensors, 17(11), 2625.1424-3210https://hdl.handle.net/10016/38617The 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.13eng© 2017 by the authors. Licensee MDPI, Basel, Switzerland.Atribución 3.0 EspañaBlind source separationElectric insulationPartial dischargesUhf detectionresearch articleElectrónicaInformáticaIngeniería IndustrialTelecomunicacioneshttps://doi.org/10.3390/s17112625open access111, 262513Sensors17AR/0000022234