Wavelet packet transform and improved complete ensemble empirical mode decomposition with adaptive noise based power quality disturbance detection

Given the low accuracy of power quality disturbance (PQD) detection, a PQD detection method based on the wavelet packet transform (WPT) and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is proposed in this paper. First, the wavelet packet transform is used to preprocess the signal to suppress noise interference. Then, ICEEMDAN technology is adopted to calculate the local mean value by adding adaptive noise. In addition, different intrinsic mode functions (IMFs) are obtained through residual subtraction. Furthermore, the effective IMFs are calculated by the permutation entropy method to reduce false modal components and to suppress residual noise. Finally, a Hilbert transform (HT) is performed to extract the detection signal parameters. The obtained results demonstrate that this method can improve the detection accuracy and PQD speed, which results in a strong anti-noise capability.

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Cite this article

[IEEE Style]

Y. Mei, Y. Wang, X. Zhang, S. Liu, Q. Wei, Z. Dou, "Wavelet packet transform and improved complete ensemble empirical mode decomposition with adaptive noise based power quality disturbance detection," Journal of Power Electronics, vol. 22, no. 8, pp. 1334-1346, 2022. DOI: 10.1007/s43236-022-00440-y.

[ACM Style]

Yu Mei, Yajing Wang, Xiangke Zhang, Shiqi Liu, Qinqin Wei, and Zhenhai Dou. 2022. Wavelet packet transform and improved complete ensemble empirical mode decomposition with adaptive noise based power quality disturbance detection. Journal of Power Electronics, 22, 8, (2022), 1334-1346. DOI: 10.1007/s43236-022-00440-y.