An incremental knowledge based approach to the analysis of partial discharge data

S.E. Rudd, S. Strachan, M.D. Judd, S.D.J. McArthur

Research output: Contribution to conferencePaper

Abstract

Defects in transformer insulation cause partial discharges (PD) which over time can progressively deteriorate the insulating material and possibly lead to electrical breakdown. Therefore, the early detection of the PD is crucial. A PD emits an electromagnetic signal in the ultra high frequency range, and current digital hardware has made it possible to transform this raw data into Phase-Resolved Partial Discharge (PRPD) pattern. Automated PD diagnositc systems previously employed pattern recognition techniques. However, specialists are now able to identify features of the PRPD pattern and deduce different behaviours and therefore physical geometical aspects of the defect. Using this knowledge within a knowledge-based system provides and explanation, and therefore reassurance of the diagnosed fault. This paper describes how to capture and model the knowledge from experts, along with the construction of a rule-based system. It presents a case study of the system's use and the introduction of explanation when diagnosing a defect. The next stage of the monitoring process involves linking the online PD data capture to further diagnostic algorithms and user interfaces. This paper illustrates how this knowledge-based system integrates into an overall transformer monitoring system to provide further data handling and interpretation.

Conference

Conference15th International Symposium on High Voltage Engineering
Abbreviated titleISH2007
CountrySlovenia
CityLjubljana
Period27/08/0731/08/07

Fingerprint

Partial discharges
Knowledge based systems
Defects
Data handling
Insulating materials
Process monitoring
User interfaces
Pattern recognition
Insulation
Data acquisition
Hardware
Monitoring

Keywords

  • partial discharge data
  • knowledge based approach
  • analysis

Cite this

Rudd, S. E., Strachan, S., Judd, M. D., & McArthur, S. D. J. (2007). An incremental knowledge based approach to the analysis of partial discharge data. Paper presented at 15th International Symposium on High Voltage Engineering, Ljubljana, Slovenia.
Rudd, S.E. ; Strachan, S. ; Judd, M.D. ; McArthur, S.D.J. / An incremental knowledge based approach to the analysis of partial discharge data. Paper presented at 15th International Symposium on High Voltage Engineering, Ljubljana, Slovenia.6 p.
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abstract = "Defects in transformer insulation cause partial discharges (PD) which over time can progressively deteriorate the insulating material and possibly lead to electrical breakdown. Therefore, the early detection of the PD is crucial. A PD emits an electromagnetic signal in the ultra high frequency range, and current digital hardware has made it possible to transform this raw data into Phase-Resolved Partial Discharge (PRPD) pattern. Automated PD diagnositc systems previously employed pattern recognition techniques. However, specialists are now able to identify features of the PRPD pattern and deduce different behaviours and therefore physical geometical aspects of the defect. Using this knowledge within a knowledge-based system provides and explanation, and therefore reassurance of the diagnosed fault. This paper describes how to capture and model the knowledge from experts, along with the construction of a rule-based system. It presents a case study of the system's use and the introduction of explanation when diagnosing a defect. The next stage of the monitoring process involves linking the online PD data capture to further diagnostic algorithms and user interfaces. This paper illustrates how this knowledge-based system integrates into an overall transformer monitoring system to provide further data handling and interpretation.",
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note = "15th International Symposium on High Voltage Engineering, ISH2007 ; Conference date: 27-08-2007 Through 31-08-2007",

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Rudd, SE, Strachan, S, Judd, MD & McArthur, SDJ 2007, 'An incremental knowledge based approach to the analysis of partial discharge data' Paper presented at 15th International Symposium on High Voltage Engineering, Ljubljana, Slovenia, 27/08/07 - 31/08/07, .

An incremental knowledge based approach to the analysis of partial discharge data. / Rudd, S.E.; Strachan, S.; Judd, M.D.; McArthur, S.D.J.

2007. Paper presented at 15th International Symposium on High Voltage Engineering, Ljubljana, Slovenia.

Research output: Contribution to conferencePaper

TY - CONF

T1 - An incremental knowledge based approach to the analysis of partial discharge data

AU - Rudd, S.E.

AU - Strachan, S.

AU - Judd, M.D.

AU - McArthur, S.D.J.

PY - 2007

Y1 - 2007

N2 - Defects in transformer insulation cause partial discharges (PD) which over time can progressively deteriorate the insulating material and possibly lead to electrical breakdown. Therefore, the early detection of the PD is crucial. A PD emits an electromagnetic signal in the ultra high frequency range, and current digital hardware has made it possible to transform this raw data into Phase-Resolved Partial Discharge (PRPD) pattern. Automated PD diagnositc systems previously employed pattern recognition techniques. However, specialists are now able to identify features of the PRPD pattern and deduce different behaviours and therefore physical geometical aspects of the defect. Using this knowledge within a knowledge-based system provides and explanation, and therefore reassurance of the diagnosed fault. This paper describes how to capture and model the knowledge from experts, along with the construction of a rule-based system. It presents a case study of the system's use and the introduction of explanation when diagnosing a defect. The next stage of the monitoring process involves linking the online PD data capture to further diagnostic algorithms and user interfaces. This paper illustrates how this knowledge-based system integrates into an overall transformer monitoring system to provide further data handling and interpretation.

AB - Defects in transformer insulation cause partial discharges (PD) which over time can progressively deteriorate the insulating material and possibly lead to electrical breakdown. Therefore, the early detection of the PD is crucial. A PD emits an electromagnetic signal in the ultra high frequency range, and current digital hardware has made it possible to transform this raw data into Phase-Resolved Partial Discharge (PRPD) pattern. Automated PD diagnositc systems previously employed pattern recognition techniques. However, specialists are now able to identify features of the PRPD pattern and deduce different behaviours and therefore physical geometical aspects of the defect. Using this knowledge within a knowledge-based system provides and explanation, and therefore reassurance of the diagnosed fault. This paper describes how to capture and model the knowledge from experts, along with the construction of a rule-based system. It presents a case study of the system's use and the introduction of explanation when diagnosing a defect. The next stage of the monitoring process involves linking the online PD data capture to further diagnostic algorithms and user interfaces. This paper illustrates how this knowledge-based system integrates into an overall transformer monitoring system to provide further data handling and interpretation.

KW - partial discharge data

KW - knowledge based approach

KW - analysis

M3 - Paper

ER -

Rudd SE, Strachan S, Judd MD, McArthur SDJ. An incremental knowledge based approach to the analysis of partial discharge data. 2007. Paper presented at 15th International Symposium on High Voltage Engineering, Ljubljana, Slovenia.