Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy

被引:86
|
作者
An, Xueli [1 ]
Yang, Junjie [2 ]
机构
[1] China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China
[2] Lingnan Normal Univ, Sch Informat Sci & Technol, Zhanjiang, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Approximate entropy; denoising; hydropower unit; variational mode decomposition; vibration signal; WAVELET TRANSFORM;
D O I
10.1177/0142331215592064
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A denoising method for a hydropower unit vibration signal based on variational mode decomposition (VMD) and approximate entropy is proposed. The signal was decomposed by VMD into discrete numbers of modes, then the approximate entropy of each mode was computed. These modes were reconstructed according to a preset threshold of the approximate entropy. Finally, the denoising of the hydropower unit vibration signal can be achieved. A simulation signal and real signals of hydropower unit vibration were used to verify the proposed method. The results showed that the proposed method had a good denoising performance and was better than the wavelet transform method in the signal-to-noise ratio (SNR), root mean square error (RMSE) and partial correlation index. It was ideally suited for the online denoising of the hydropower unit vibration signal.
引用
收藏
页码:282 / 292
页数:11
相关论文
共 50 条
  • [1] Application of adaptive local iterative filtering and approximate entropy to vibration signal denoising of hydropower unit
    An, Xueli
    Li, Chaoshun
    Zhang, Fei
    [J]. JOURNAL OF VIBROENGINEERING, 2016, 18 (07) : 4299 - 4311
  • [2] Analysis of hydropower unit vibration signals based on variational mode decomposition
    An, Xueli
    Pan, Luoping
    Zhang, Fei
    [J]. JOURNAL OF VIBRATION AND CONTROL, 2017, 23 (12) : 1938 - 1953
  • [3] Forecasting the hydropower unit vibration based on adaptive variational mode decomposition and neural network
    Lu, Zhaoheng
    Tao, Ran
    Xiao, Ruofu
    Li, Puxi
    [J]. APPLIED SOFT COMPUTING, 2024, 150
  • [4] Microseismic signal denoising by combining variational mode decomposition with permutation entropy
    Zhang Xing-Li
    Cao Lian-Yue
    Chen Yan
    Jia Rui-Sheng
    Lu Xin-Ming
    [J]. APPLIED GEOPHYSICS, 2022, 19 (01) : 65 - 80
  • [5] Microseismic signal denoising by combining variational mode decomposition with permutation entropy
    Zhang Xing-Li
    Cao Lian-Yue
    Chen Yan
    Jia Rui-Sheng
    Lu Xin-Ming
    [J]. Applied Geophysics, 2022, 19 : 65 - 80
  • [6] A method of eliminating the vibration signal noise of hydropower unit based on NA-MEMD and approximate entropy
    An, Xueli
    Yang, Junjie
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING, 2017, 231 (02) : 317 - 328
  • [7] A Vibration Signal Denoising Method of Marine Atomic Gravimeter Based on Improved Variational Mode Decomposition
    Gong, Wenbin
    Li, An
    Liao, An
    Che, Hao
    Huang, Chunfu
    Qin, Fangjun
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [8] Signal Denoising Based on Wavelet Threshold Denoising and Optimized Variational Mode Decomposition
    Hu, Hongping
    Ao, Yan
    Yan, Huichao
    Bai, Yanping
    Shi, Na
    [J]. JOURNAL OF SENSORS, 2021, 2021
  • [9] Wavelet Denoising for the Vibration Signals of Wind Turbines Based on Variational Mode Decomposition and Multiscale Permutation Entropy
    Chen, Xuejun
    Yang, Yongming
    Cui, Zhixin
    Shen, Jun
    [J]. IEEE ACCESS, 2020, 8 : 40347 - 40356
  • [10] Micro-Vibration Signal Denoising Algorithm of Spectral Morphology Fitting Based on Variational Mode Decomposition
    Yu, Caizhi
    Lu, Yutai
    Li, Yue
    Wang, Peng
    Sun, Changku
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (24):