| Abstract: |
| The paper deals with the application of Volterra bound Interval type −2 fuzzy logic techniques in power quality
assessment. This work proposes a new layout for detection, localization and classification of various types of power
quality events. The proposed method exploits Volterra series for the extraction of relevant features, which are used
to recognize different PQ events by Interval type-2 fuzzy logic based classifier. Numerous single as well as multiple
powers signal disturbances have been simulated to testify the efficiency of the proposed technique. This time–
frequency analysis results in the clear visual detection, localization, and classification of the different power quality
events. The simulation results signify that the proposed scheme has a higher recognition rate while classifying
single and multiple power quality events unlike other methods. Finally, the proposed method is compared with
SVM, feed forward neural network and type −1 Fuzzy logic system based classifier to show the efficacy of the
proposed technique in classifying the Power quality events. |
| Key words: Non-stationary power signals, Power quality (PQ), Volterra series, Interval type-2 fuzzy logic system(IT2FLS), Power Spectral Entropy (PSE), Standard Deviation (SD) |
| DOI：10.1186/s41601-017-0039-z |
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| Fund: |
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