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Multi-source partial discharge signals discrimination by six bandpass filters and DBSCAN clustering

Firuzi, K ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/ICPADM.2018.8401079
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. Partial discharge (PD) signals generated by defects in a transformer insulation can be captured through measurement instruments and they may be used, after preprocessing, to discriminate the PD Sources. Some of the artificial defect models, such as: corona, internal cavity and surface discharge in air are developed in the laboratory. These defect models are put in parallel under a high voltage stress. The PD signals stemmed from these sets of multiple PD sources are captured. In this paper six bandpass Alters (with two MPD 600 devices) are used for feature extraction of these signals. For PD signals discrimination, the Density-Based Spatial Clustering of Applications with Noise density (DBSCAN) method is employed with two freedom parameters which resulted in an accurate discrimination of types of partial discharge sources. © 2018 IEEE
  6. Keywords:
  7. Density-based spatial clustering of applications with noise(DBSCAN) ; Partial discharge ; Bandpass filters ; Extraction ; Feature extraction ; Partial discharges ; Artificial defects ; Density based spatial clustering of applications with noise ; High-voltage stress ; Measurement instruments ; Noise density ; Partial discharge signal ; Partial discharge sources ; Transformer insulation ; Dielectric materials
  8. Source: Proceedings of the IEEE International Conference on Properties and Applications of Dielectric Materials, 20 May 2018 through 24 May 2018 ; Volume 2018-May , 2018 , Pages 68-71 ; 2160-9241 (Electronic ISSN) ; 9781538657881 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/8401079