A Comprehensive Overview on Modified Versions of Stockwell Transform For Power Quality Monitoring

The increasing trends toward the accurate identification of power quality disturbances (PQD) via (PQ) monitoring require an appropriate digital signal processing (DSP) technique and a robust classifier. To this end, Stockwell transform (ST), one most efficient feature extraction DSP tools, its several variants play utmost role in PQ assessment framework. Its time-varying spectral characteristics generally extract local instantaneous frequency spectrum from global temporary behavior PQD signal. However, Standard ST suffers thepoor time-frequency resolution because frequency-dependent Gaussian window (GW). While analysis statistically signals requires suitable balance between time resolution. paper provides comprehensive literature review on modified versions for first to reduce computational complexity algorithm as well maximize energy concentration plane. A comparative all STs has been presented tabular form provide key each technique. Additionally, case study substantiate highest accuracy proposed over other variants. Apart classification, miscellaneous applications have indicated. This may valuable resource researchers further improvement not only classifying but also wide applications.