Literature DB >> 28134812

A Novel Method for Separating and Locating Multiple Partial Discharge Sources in a Substation.

Pengfei Li1, Wenjun Zhou2, Shuai Yang3, Yushun Liu4, Yan Tian5, Yong Wang6.   

Abstract

To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low, and the localization result was a coordinate on two-dimensional plane. In this paper, a novel method is proposed to improve the separation rate and the localization accuracy. A directional measuring platform is built using two directional antennas. The time delay (TD) of the signals captured by the antennas is calculated, and TD sequences are obtained by rotating the platform at different angles. The sequences are separated with the TD distribution feature, and the directions of the multi-PD sources are calculated. The PD sources are located by directions using the error probability method. To verify the method, a simulated model with three PD sources was established by XFdtd. Simulation results show that the separation rate is increased from 71% to 95% compared with the previous method, and an accurate three-dimensional localization result was obtained. A field test with two PD sources was carried out, and the sources were separated and located accurately by the proposed method.

Entities:  

Keywords:  error probability; multi-point measuring direction; multiple PD sources separation; partial discharge localization; substation

Year:  2017        PMID: 28134812      PMCID: PMC5335984          DOI: 10.3390/s17020247

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Machine learning. Clustering by fast search and find of density peaks.

Authors:  Alex Rodriguez; Alessandro Laio
Journal:  Science       Date:  2014-06-27       Impact factor: 47.728

2.  An Ultrahigh Frequency Partial Discharge Signal De-Noising Method Based on a Generalized S-Transform and Module Time-Frequency Matrix.

Authors:  Yushun Liu; Wenjun Zhou; Pengfei Li; Shuai Yang; Yan Tian
Journal:  Sensors (Basel)       Date:  2016-06-22       Impact factor: 3.576

  2 in total
  2 in total

1.  Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization.

Authors:  Guillermo Robles; José Manuel Fresno; Juan Manuel Martínez-Tarifa; Jorge Alfredo Ardila-Rey; Emilio Parrado-Hernández
Journal:  Sensors (Basel)       Date:  2018-03-01       Impact factor: 3.576

2.  Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers.

Authors:  Guillermo Robles; José Manuel Fresno; Juan Manuel Martínez-Tarifa
Journal:  Sensors (Basel)       Date:  2018-05-03       Impact factor: 3.576

  2 in total

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