基于EEMD的HHT在电能质量多扰动分类识别中的应用

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Abstract For the reason that existing classification and recognition methods of power quality multi-disturbance have lower classification accuracy and recognition ability, the EEMD-HHT method is introduced to classifying the power quality multi-disturbance, which is based on the characteristics of power quality multi-disturbance. Firstly, the signal was decomposed into Intrinsic Mode Function (IMF) by the EEMD. Then the noise in the components is suppressed through thresholding and reconstructing each IMF with adaptive thresholds. Finally, the instantaneous attributes and start-stop time of the power quality multi-disturbance signals can be extracted with Hilbert transform. Simulation results in matlab show that the proposed method can effectively detect, locate and analyze power quality multi- disturbance.

Key words： power quality multi-disturbances hilbert huang transform ensemble empirical mode decomposition

Published: 19 April 2017

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	Articles by authors
	Cao Lingzhi
	Liu Junfei
	Zheng Xiaowan

Cite this article:

Cao Lingzhi,Liu Junfei,Zheng Xiaowan. Classification and Recognition of Power Quality Multi-disturbance based on EEMD-HHT[J]. Electrical Engineering, 2017, 18(4): 66-70.

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http://dqjs.cesmedia.cn/EN/Y2017/V18/I4/66

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