A Combined Noise Reduction Method for Floodgate Vibration Signals Based on Adaptive Singular Value Decomposition and Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

被引:2
|
作者
Wang, Wentao [1 ]
Zhu, Huiqi [1 ]
Cheng, Yingxin [1 ]
Tang, Yiyuan [1 ]
Liu, Bo [1 ]
Li, Huokun [1 ]
Yang, Fan [2 ]
Zhang, Wenyuan [2 ]
Huang, Wei [1 ]
Zheng, Fang [3 ]
机构
[1] Nanchang Univ, Sch Infrastruct Engn, Nanchang 330031, Peoples R China
[2] China Inst Water Resources & Hydropower Res, Dept Hydraul, Beijing 100038, Peoples R China
[3] China Railway Water Conservancy & Hydropower Plann, Nanchang 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
floodgates; vibration signal; noise reduction; ASVD algorithm; ICEEMDAN; IDENTIFICATION METHOD; EMD;
D O I
10.3390/w15244287
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To address the issue of the vibration characteristic signals of floodgates being affected by background white noise and low-frequency water flow noise, a noise reduction method combining the improved adaptive singular value decomposition algorithm (ASVD) and the improved complete ensemble EMD with adaptive noise (ICEEMDAN) is proposed. Firstly, a Hankel matrix is constructed based on the collected discrete time signals. After performing SVD on the Hankel matrix, the ASVD algorithm is used to automatically select the effective singular values to filter out most of the background white noise and retain the useful frequency components with similar energy in the signal. Then, ICEEMDAN combined with the Spearman correlation coefficient method is used to further filter out residual white noise and low-frequency water flows. The noise reduction performance of this combined method is verified through simulation experiments. Filtered by the ASVD-ICEEMDAN method, the signal-to-noise ratio of the simulation signal (50% noise level) is increased from 4.417 to 16.237, and the root mean square error is reduced from 2.286 to 0.586. Based on the practically measured vibration signals of a floodgate at a large hydropower station, the result shows that the ASVD-ICEEMDAN method exhibits good noise reduction performance and feature information extraction abilities for floodgate vibration signals, and can provide support for operational mode analysis and damage identification of practical structures under complex interference conditions.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Fault diagnosis of rotating machinery based on noise reduction using empirical mode decomposition and singular value decomposition
    Jiang, Fan
    Zhu, Zhencai
    Li, Wei
    Zhou, Gongbo
    Chen, Guoan
    JOURNAL OF VIBROENGINEERING, 2015, 17 (01) : 164 - 174
  • [32] RANDOM NOISE REDUCTION USING A HYBRID METHOD BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION
    Chen, Wei
    Zhang, Dong
    Chen, Yangkang
    JOURNAL OF SEISMIC EXPLORATION, 2017, 26 (03): : 227 - 249
  • [33] ATMOSPHERIC LIDAR NOISE REDUCTION BASED ON ENSEMBLE EMPIRICAL MODE DECOMPOSITION
    Li, Jun
    Gong, Wei
    Ma, Yingying
    XXII ISPRS CONGRESS, TECHNICAL COMMISSION VIII, 2012, 39-B8 : 127 - 129
  • [34] Development of an advanced noise reduction method for vibration analysis based on singular value decomposition
    Yang, WX
    Tse, PW
    NDT & E INTERNATIONAL, 2003, 36 (06) : 419 - 432
  • [35] Empirical mode decomposition based adaptive noise canceller for improved identification of exons in eukaryotes
    Malaya Kumar Hota
    Network Modeling Analysis in Health Informatics and Bioinformatics, 2021, 10
  • [36] Empirical mode decomposition based adaptive noise canceller for improved identification of exons in eukaryotes
    Hota, Malaya Kumar
    NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, 2021, 10 (01):
  • [37] Improved complete ensemble empirical mode decomposition with adaptive noise: quasi-oppositional Jaya hybrid algorithm for ECG denoising
    Bodile, Roshan M.
    Rao, T. V. K. Hanumantha
    ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 2021, 109 (02) : 467 - 477
  • [38] Hob vibration signal denoising and effective features enhancing using improved complete ensemble empirical mode decomposition with adaptive noise and fuzzy rough sets
    Zhou, Han
    Yan, Ping
    Huang, Qin
    Yuan, Yanfei
    Pei, Jie
    Yang, Yong
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 233
  • [39] Improved complete ensemble empirical mode decomposition with adaptive noise: quasi-oppositional Jaya hybrid algorithm for ECG denoising
    Roshan M. Bodile
    T. V. K. Hanumantha Rao
    Analog Integrated Circuits and Signal Processing, 2021, 109 : 467 - 477
  • [40] Series arc fault identification based on complete ensemble empirical mode decomposition with adaptive noise and convolutional neural network
    Shang T.
    Wang W.
    Peng J.
    Xu B.
    Gao H.
    Zhai G.
    International Journal of Metrology and Quality Engineering, 2022, 13