Optimized variational mode decomposition denoising method based on weighted mean of vectors algorithm

被引:1
|
作者
Wang, Dongmei [1 ,2 ,3 ]
Tong, Yingli [1 ,2 ,3 ]
Yang, Dandi [1 ,2 ,3 ]
Wang, Peng [1 ,2 ,3 ,4 ]
Lu, Jingyi [1 ,2 ,3 ,4 ]
机构
[1] Northeast Petr Univ, Sanya Marine Oil & Gas Res Inst, Sanya, Hainan, Peoples R China
[2] Northeast Petr Univ, Sch Elect Informat Engn, Daqing, Heilongjiang, Peoples R China
[3] Northeast Petr Univ, Artificial Intelligence Energy Res Inst, Daqing, Heilongjiang, Peoples R China
[4] Heilongjiang Prov Key Lab Networking & Intelligent, Daqing, Peoples R China
基金
中国国家自然科学基金;
关键词
Hausdorff distance; leakage signal; signal-to-noise ratio; variational modal decomposition; weighted mean of vectors algorithm;
D O I
10.1080/10916466.2024.2314182
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Aiming at the noise interference in oil and gas pipeline leakage detection, a signal denoising method based on improved variational mode decomposition (VMD) algorithm is proposed. First, the weighted mean of vectors algorithm (INFO) is used to select the parameters of the VMD algorithm adaptively to obtain the best decomposition level K value and penalty factor alpha value, which effectively solves the problem that the parameters are difficult to select in VMD. Then, according to the Hausdorff distance between the original signal and the probability density of each IMF, the effective modal components are selected for reconstruction and denoising signal is obtained. In oil and gas pipeline leakage signal processing, compared with whale optimization algorithm, grey wolf optimization algorithm, and particle swarm optimization algorithm, the reconstructed signal obtained by the proposed INFO algorithm optimized VMD parameters has higher signal-to-noise ratio and lower mean square error and mean absolute error. It shows that the proposed algorithm has better denoising effect.
引用
收藏
页码:949 / 966
页数:18
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