Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2000-03-06
2001-02-20
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C324S536000
Reexamination Certificate
active
06192317
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention relates to quality assessment and condition monitoring of electrical insulation and more particularly to statistical pattern analysis and diagnostics of partial discharge measurements of high voltage insulation.
Partial discharge (PD) analysis has been established as a useful diagnostic tool to asses high voltage insulation systems for integrity and design deficiencies. Interpretation of the PD patterns can reveal the source and the reason for the PD pattern occurrence, and therefore, has been used as a condition monitoring and quality control tool by the manufacturing industry. Analysis of PD patterns for high voltage electrical equipment has often times been an heuristic process based on empirical reasoning and anecdotal information. This is particularly true for insulation systems encountered in high voltage rotating machinery. Typically high voltage insulation is a heterogeneous composite comprising tape, mica flakes, and resin. No insulation system is perfect and there is a statistical distribution of voids and other defects throughout the insulation system. This void distribution results in a baseline level of PD activity for all insulation systems. The associated discharge phenomena are often complicated, multi-faceted events. Discerning between “normal” and defective insulation systems often require more than simple trending of discharge levels.
For many years, the use of PD results for insulation was impracticable because of the difficult data manipulation problems presented. It is thus desirable to identify defective high voltage electrical equipment by the analysis of PD events in an effective and economic manner.
Typically, users of expensive high voltage electrical equipment incur extraordinary expenses when the equipment unexpectedly fails. The ability to predict failures of this equipment would enable the equipment user to utilize condition-based maintenance techniques to avert such unexpected failures and associated high costs. Additionally, scheduled maintenance plans cause users to incur unnecessary costs when equipment is found to be functioning satisfactorily after the scheduled maintenance. Therefore, there exists a need to monitor high voltage insulation when the high voltage equipment is in operation to predict when a catastrophic defect will occur so as to avoid excessive damage and unexpected and costly repair of the high voltage electrical equipment caused by the defect.
There exists a need to identify when a defect exits in insulation before it is placed in the high voltage equipment by assessing the quality of the insulation. It is also desirable to identify the type of defect in the insulation after it is detected.
SUMMARY OF THE INVENTION
The present invention addresses the foregoing needs by providing a system for evaluation of the insulation system of high voltage equipment, including quality assessment and condition monitoring.
The quality assessment method includes extracting representative quality class thresholds from partial discharge (PD) measurements of known insulation quality during a training stage. These quality class representatives and quality class thresholds from the baseline are used for comparison to analysis features of partial discharge test data to assess the quality of undetermined insulation. Histogram similarity measures are utilized to determine the representatives of the quality class thresholds of each insulation quality type.
The condition monitoring method includes collecting periodic PD measurements of insulation during the normal operation of high voltage equipment. Trend analysis is employed to identify any deviation from an expected baseline of high voltage electrical equipment.
Krahn John Raymond
Yazici Birsen
Breedlove Jill M.
General Electric Company
Hoff Marc S.
Miller Craig Steven
Thompson John F.
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