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Online condition monitoring of HV cable circuits

Online condition monitoring of HV cable circuits
Online condition monitoring of HV cable circuits

This thesis is concerned with the development of online condition monitoring methods for high voltage cables and accessories.  In particular the detection and measurement of partial discharge activities has been investigated in detail as it is an important metric and a clear symptom of insulation degradation.

Acoustic methods have been widely applied for partial discharge detection in power apparatus.  Initial studies were undertaken to assess the suitability of PVDF as a piezoelectric sensor for detecting acoustic emission signals due to partial discharge activities in high voltage cable accessories.  However, experimentation revealed that in this application the sensor output is due to electrical coupling rather than measuring a detectable acoustic emission signal.

As an alternative approach, the use of capacitive couplers for partial discharge detection has been further considered.  Although widely applied a suitably accurate method of calibration when used in the field has not been developed.  Assessment of various pulse based calibration techniques yielded the conclusion that these approaches are inaccurate because they cannot account for the influence of stray capacitance. This has led to the development of a new method of calibration based on frequency response analysis and the use of simulation model.  Results obtained are in good agreement with values determined using a terminal injection method.

Consideration has also been given to methods of discriminating between internal partial discharge activities and external sources of noise such as corona discharge, synchronous pulses or random noise.  The use of wavelets for signals discrimination and to improve the signal to noise ratio has proved successful.

University of Southampton
Wang, Ping
5f7a5780-5969-4486-ab0c-c527e48b3c34
Wang, Ping
5f7a5780-5969-4486-ab0c-c527e48b3c34

Wang, Ping (2004) Online condition monitoring of HV cable circuits. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

This thesis is concerned with the development of online condition monitoring methods for high voltage cables and accessories.  In particular the detection and measurement of partial discharge activities has been investigated in detail as it is an important metric and a clear symptom of insulation degradation.

Acoustic methods have been widely applied for partial discharge detection in power apparatus.  Initial studies were undertaken to assess the suitability of PVDF as a piezoelectric sensor for detecting acoustic emission signals due to partial discharge activities in high voltage cable accessories.  However, experimentation revealed that in this application the sensor output is due to electrical coupling rather than measuring a detectable acoustic emission signal.

As an alternative approach, the use of capacitive couplers for partial discharge detection has been further considered.  Although widely applied a suitably accurate method of calibration when used in the field has not been developed.  Assessment of various pulse based calibration techniques yielded the conclusion that these approaches are inaccurate because they cannot account for the influence of stray capacitance. This has led to the development of a new method of calibration based on frequency response analysis and the use of simulation model.  Results obtained are in good agreement with values determined using a terminal injection method.

Consideration has also been given to methods of discriminating between internal partial discharge activities and external sources of noise such as corona discharge, synchronous pulses or random noise.  The use of wavelets for signals discrimination and to improve the signal to noise ratio has proved successful.

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Published date: 2004

Identifiers

Local EPrints ID: 465666
URI: http://eprints.soton.ac.uk/id/eprint/465666
PURE UUID: 41d9e637-abe3-407f-9e37-a77c018248fd

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Date deposited: 05 Jul 2022 02:30
Last modified: 16 Mar 2024 20:18

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Contributors

Author: Ping Wang

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