Event Detection and Its Signal Characterization in PMU Data Stream

The potential application of signal processing techniques is not only to detect the event but also to characterize them according to physical disturbance. In this paper, event detection and its characterization algorithm is presented. The event detection scheme uses computation of spectral kurtosis on sum of intrinsic mode functions. The algorithm is capable of detecting the event in phasor measurement units data by comparing the maximum energy and root-mean square of energy content of present analysis segment with respect to previous segment. The statistical indices applied are capable to flag specific data and thus the timely detection of events. Further, statistical features extracted from event-related segment suggest that the transient signals from different regions are distinct and thus can be classified. The signal characterization is further represented in terms of short-term energy and group delay. The analysis on event triggered signal demonstrates the related physical phenomenon in each event type. The study suggests the most relevant signal associated with a particular type of event.

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