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

fr a me-based event model. Results and experiences

made by a test in a low-voltage power

system are presented.