Feng Zhao1,2, Di Liao1,*, Xiaoqiang Chen1,2, Ying Wang1,2
Energy Engineering, Vol.120, No.5, pp. 1133-1148, 2023, DOI:10.32604/ee.2023.025900
- 20 February 2023
Abstract Aiming at the problems of multiple types of power quality composite disturbances, strong feature correlation and high recognition error rate, a method of power quality composite disturbances identification based on multi-resolution S-transform and decision tree was proposed. Firstly, according to IEEE standard, the signal models of seven single power quality disturbances and 17 combined power quality disturbances are given, and the disturbance waveform samples are generated in batches. Then, in order to improve the recognition accuracy, the adjustment factor is introduced to obtain the controllable time-frequency resolution through multi-resolution S-transform time-frequency domain analysis. On this… More >
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