Application of a noise reduction method combining AVMD and SVD in natural gas pipeline leakage signal

被引:4
|
作者
Lu, Jingyi [1 ,2 ]
Qu, Xue [3 ]
Wang, Dongmei [3 ]
Yue, Jikang [3 ]
Zhu, Lijuan [3 ]
Li, Gongfa [4 ]
机构
[1] Northeast Petr Univ, Artificial Intelligence Energy Res Inst, Daqing, Peoples R China
[2] Northeast Petr Univ, Heilongjiang Prov Key Lab Networking & Intelligen, Daqing, Peoples R China
[3] Northeast Petr Univ, Coll Elect & Informat Engn, Daqing, Peoples R China
[4] Wuhan Univ Sci & Technol, Key Lab Met Equipment & Control, Minist Educ, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Variational mode decomposition; parameter optimization; signal denoising; pipeline leakage;
D O I
10.1080/21642583.2021.1913450
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the large amount of noise in pipeline leakage signal, the accuracy of the leakage detection device's judgment will be reduced by direct leakage detection. Therefore, the noise reduction of pipeline leakage signal is critical for preprocessing technology of pipeline leakage detection. A denoising method combining adaptive variational mode decomposition (AVMD) and singular value decomposition (SVD) is proposed in this paper. First, the mode number and the penalty factor of VMD are searched automatically by AVMD. The AVMD algorithm is coupled to a fitness function based on improved refine composite multiscale dispersion entropy (RCMDE). Subsequently, a time-frequency matrix which obtains time-frequency subspace after SVD is constructed for all mode components decomposed by VMD, and the number of effective time-frequency subspaces is determined by the relative change rate of singular values, thereby the denoised signal is achieved. Finally, the experimental results show that the AVMD-SVD method proposed in this paper has the significant denoising effect and strong robustness.
引用
收藏
页码:380 / 392
页数:13
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