Abstract

In power quality investigations, triggered waveforms often claim the spotlight, but it is the stripchart that tells the story of the entire recording. Reviewing this data manually is tedious, error-prone, and lacks context. Merlin™ applies AI-driven pattern recognition to the full stripchart, automatically examining voltage and current behavior across all phases to determine root cause and attribution. This white paper explores how Merlin™ organizes stripchart findings into six distinct analysis modules — Voltage Sags, Voltage Swells, Loose Neutrals, Voltage Regulation, Flicker, and Harmonics — delivering specific, actionable conclusions rather than raw statistics.