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Article

Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation

1
Department of Electronic Technology, Universidad Carlos III de Madrid, Avda, Universidad, 30, 28911 Leganés, Madrid, Spain
2
Department of Electrical Engineering, Universidad Carlos III de Madrid, Avda, Universidad, 30, 28911 Leganés, Madrid, Spain
3
Department of Signal Processing and Communications, Universidad Carlos III de Madrid, Avda, Universidad, 30, 28911 Leganés, Madrid, Spain
*
Author to whom correspondence should be addressed.
Sensors 2017, 17(11), 2625; https://doi.org/10.3390/s17112625
Received: 16 October 2017 / Revised: 10 November 2017 / Accepted: 10 November 2017 / Published: 15 November 2017
(This article belongs to the Special Issue UHF and RF Sensor Technology for Partial Discharge Detection)
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. View Full-Text
Keywords: blind source separation; electric insulation; partial discharges; UHF detection blind source separation; electric insulation; partial discharges; UHF detection
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MDPI and ACS Style

Boya, C.; Robles, G.; Parrado-Hernández, E.; Ruiz-Llata, M. Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation. Sensors 2017, 17, 2625. https://doi.org/10.3390/s17112625

AMA Style

Boya C, Robles G, Parrado-Hernández E, Ruiz-Llata M. Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation. Sensors. 2017; 17(11):2625. https://doi.org/10.3390/s17112625

Chicago/Turabian Style

Boya, Carlos, Guillermo Robles, Emilio Parrado-Hernández, and Marta Ruiz-Llata. 2017. "Detection of Partial Discharge Sources Using UHF Sensors and Blind Signal Separation" Sensors 17, no. 11: 2625. https://doi.org/10.3390/s17112625

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