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Multisource PD identification based on phase synchronous and asynchronous data

Multisource PD identification based on phase synchronous and asynchronous data
Multisource PD identification based on phase synchronous and asynchronous data
Partial Discharge (PD) measurements in cables and their accessories play a fundamental role in Condition Based Monitoring (CBM) of High Voltage (HV) equipment. CBM monitoring has been enforced by utilities in the transmission and distribution (T&D) environment as part of a predictive maintenance program that aims to result in less unscheduled downtime and lower maintenance cost. Identifying the source of a PD rather than merely assessing its magnitude provides additional information that could enable more educated decisions concerning the integrity of the insulation to be made. In on-line scenarios the presence of multiple PD sources that are simultaneously active as well as the presence of interference, complicates the identification process. In this paper, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm has been employed to identify PDs of different sources. Phase synchronous measurements were acquired in the laboratory and pre-processed through a peak detection algorithm to extract the single pulses (phase asynchronous). To extract a feature the Wavelet Packet Transform (WPT) and Higher Order Statistics (HOS) were employed according to previous work by the authors. The feature was then analyzed by the Principal Component Analysis (PCA) for dimensionality reduction and study of different PD sources has been shown to form separate clusters. Application of this method on on-line data acquired from the network of the Electricity Authority of Cyprus (EAC) has demonstrated its potential use in PD identification and interference rejection.
460-463
Evagorou, D
0971dcb8-7498-499a-846c-c571414be103
Kyprianou, A
3ce6d975-3c30-4a93-9d08-59fa5dc00c36
Georghiou, G E
c3e9a8c7-a175-4d3c-aa20-e851d441c30d
Hao, L
e6006548-3fc1-4a7e-9df4-a4e9a9a05c45
Lewin, P
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Stavrou, A
88f5bae6-fb3e-4c97-8acc-6a19508e8807
Evagorou, D
0971dcb8-7498-499a-846c-c571414be103
Kyprianou, A
3ce6d975-3c30-4a93-9d08-59fa5dc00c36
Georghiou, G E
c3e9a8c7-a175-4d3c-aa20-e851d441c30d
Hao, L
e6006548-3fc1-4a7e-9df4-a4e9a9a05c45
Lewin, P
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Stavrou, A
88f5bae6-fb3e-4c97-8acc-6a19508e8807

Evagorou, D, Kyprianou, A, Georghiou, G E, Hao, L, Lewin, P and Stavrou, A (2011) Multisource PD identification based on phase synchronous and asynchronous data. 2011 Conference on Electrical Insulation and Dielectric Phenomena, Cancun, Mexico. 15 - 18 Oct 2011. pp. 460-463 . (doi:10.1109/CEIDP.2011.6232694).

Record type: Conference or Workshop Item (Paper)

Abstract

Partial Discharge (PD) measurements in cables and their accessories play a fundamental role in Condition Based Monitoring (CBM) of High Voltage (HV) equipment. CBM monitoring has been enforced by utilities in the transmission and distribution (T&D) environment as part of a predictive maintenance program that aims to result in less unscheduled downtime and lower maintenance cost. Identifying the source of a PD rather than merely assessing its magnitude provides additional information that could enable more educated decisions concerning the integrity of the insulation to be made. In on-line scenarios the presence of multiple PD sources that are simultaneously active as well as the presence of interference, complicates the identification process. In this paper, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm has been employed to identify PDs of different sources. Phase synchronous measurements were acquired in the laboratory and pre-processed through a peak detection algorithm to extract the single pulses (phase asynchronous). To extract a feature the Wavelet Packet Transform (WPT) and Higher Order Statistics (HOS) were employed according to previous work by the authors. The feature was then analyzed by the Principal Component Analysis (PCA) for dimensionality reduction and study of different PD sources has been shown to form separate clusters. Application of this method on on-line data acquired from the network of the Electricity Authority of Cyprus (EAC) has demonstrated its potential use in PD identification and interference rejection.

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More information

Published date: 16 October 2011
Additional Information: Event Dates: 16-19 October 2011
Venue - Dates: 2011 Conference on Electrical Insulation and Dielectric Phenomena, Cancun, Mexico, 2011-10-15 - 2011-10-18
Organisations: Electronics & Computer Science, EEE

Identifiers

Local EPrints ID: 272947
URI: http://eprints.soton.ac.uk/id/eprint/272947
PURE UUID: f065805d-f26b-4242-9b53-c7496276ae33
ORCID for P Lewin: ORCID iD orcid.org/0000-0002-3299-2556

Catalogue record

Date deposited: 20 Oct 2011 14:33
Last modified: 03 Dec 2021 02:35

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Contributors

Author: D Evagorou
Author: A Kyprianou
Author: G E Georghiou
Author: L Hao
Author: P Lewin ORCID iD
Author: A Stavrou

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