Abstract
This paper describes a model-based diagnostic system for diagnosing faults in Electrical Transmission Systems (Timely's off-line system). This diagnostic system uses data available from digital fault recorders which are collected after a network event (such as a short circuit) has occurred. The data are used to detect incipient faults in network equipment by comparing their operation against that predicted by extended finite state automaton known as Augmented Reactive Models (ARM). Thus Timely's off-line system combines signal processing and model based diagnostic techniques to provide a practical modelbased system that aids the analysis of the performance of protective equipment after a network event has occurred. In particular, its use of data derived directly from fault recorder files (such as voltage and impedance magnitudes) means that the system can diagnose much more subtle faults (e.g. timing related faults). © 2000 IEEE.
Original language | English |
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Pages (from-to) | 1388-1393 |
Number of pages | 6 |
Journal | IEEE Transactions on Power Systems |
Volume | 15 |
Issue number | 4 |
DOIs | |
Publication status | Published - Nov 2000 |
Keywords
- Fault recorder data
- High-voltage transmission networks
- Model-based diagnosis