@Article{ee.2022.018448,
AUTHOR = {Huakun Que, Guolong Lin, Wenchong Guo, Xiaofeng Feng, Zetao Jiang, Yunfei Cao, Jinmin Fan, Zhixian Ni},
TITLE = {Study of Denoising in the Electricity Anti-Stealing Detection Based on VMD-WTD Combination},
JOURNAL = {Energy Engineering},
VOLUME = {119},
YEAR = {2022},
NUMBER = {4},
PAGES = {1453--1466},
URL = {http://www.techscience.com/energy/v119n4/47886},
ISSN = {1546-0118},
ABSTRACT = {In order to solve the failure of electricity anti-stealing detection device triggered by the noise mixed in high-frequency electricity stealing signals, a denoising method based on variational mode decomposition (VMD) and wavelet threshold denoising (WTD) was applied to extract the effective high-frequency electricity stealing signals. First, the signal polluted by noise was pre-decomposed using the VMD algorithm, the instantaneous frequency means of each pre-decomposed components was analyzed, so as to determine the optimal K value. The optimal K value was used to decompose the polluted signal into K intrinsic mode components, and the sensitive mode components were determined through the cross-correlation function. Next, each sensitive mode was reconstructed. Finally, the reconstructed signal denoised using the wavelet threshold to obtain the denoised signal. The simulation analysis and experimental results show that the proposed method is superior to the traditional VMD method, FFT method and EMD method, as it can effectively eliminate the noise and enhance the reliability of high-frequency electricity stealing signal detection.},
DOI = {10.32604/ee.2022.018448}
}