Description: Power quality monitoring has advanced
to an important tool for system evaluation
and solving power-related problems. As a
consequence the increased amount of recorded
data requires more sophisticated analysis methods.
The paper proposes a system for automated
recording and classification of power
quality disturbances. The system features statistical
classification techniques applied to a
frame-based event model. Results and experiences
made by a test in a low-voltage power
system are presented.
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