Noise Reduction Study of Pressure Pulsation in Pumped Storage Units Based on Sparrow Optimization VMD Combined with SVD

Yan Ren, Linlin Zhang, Jiangtao Chen, Jinwei Liu, Pan Liu, Ruoyu Qiao, Xianhe Yao, Shangchen Hou, Xiaokai Li, Chunyong Cao and Hongping Chen
Additional contact information
Yan Ren: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Linlin Zhang: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Jiangtao Chen: Energy and Power Engineering Institute, Zhengzhou Electric Power College, Zhengzhou 450000, China
Jinwei Liu: China Nuclear Power Engineering Co., Ltd., Shenzhen 518124, China
Pan Liu: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Ruoyu Qiao: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Xianhe Yao: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Shangchen Hou: School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Xiaokai Li: State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China
Chunyong Cao: Hunan Heimifeng Pumped Storage Power Co., Ltd., State Grid Xin Yuan Company, Changsha 410213, China
Hongping Chen: State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China

Energies, 2022, vol. 15, issue 6, 1-18

Abstract: The unbalanced forces generated by pumped storage units operating under non-ideal operating conditions can cause pressure pulsations. Due to the noise interference, the feature information reflecting the operating state of the unit in the pressure pulsation is difficult to extract. Therefore, this paper proposes a noise reduction method based on sparrow search algorithm (SSA) optimized variational mode decomposition (VMD) combined with singular value decomposition (SVD). Firstly, SSA is used to realize the adaptive optimization of VMD parameters for ideal decomposition of the signal. Then, the noise reduction of the decomposed signal is performed by using the sensitivity of the Permutation Entropy (PE) for small mutations. The noise reduction and reconstruction of the decomposed signal are carried out again by using SVD. The experimental and comparison results show that the mean square error of the signal after VMD-SVD feature extraction is reduced from 1.0068 to 0.0732 and the correlation coefficient is increased from 0.2428 to 0.9614. It is proved that the method achieves better results in the pressure pulsation signal of pumped storage units and has some application significance for the fault diagnosis of pumped storage units.

Keywords: pumped storage units; pressure pulsation; noise reduction; variational mode decomposition; sparrow search algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/6/2073/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/6/2073/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:6:p:2073-:d:769590

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().