The Mystery Curve: A Signal Processing Based Power Quality Disturbance Detection

Abstract

In this article, detection of power quality disturbances (PQD) in the power system utilizing mystery curves has been discussed. This technique first estimates the analytic signal of the real valued input signals based on Hilbert transform. By representing polar form of such a signal which is identified as magnitude and frequency variations, informative mystery curves in two-dimension can be discovered. Through the Euler's rotation hypothesis, the two-dimensional curves can be reached out to three dimension directly. The results obtained using the synthetic signals generated in MATLAB are validated experimentally on a prototype test bench to analyze the PQD events adhering to IEEE Std. 1159-1995.