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The VMTES: Application to the structural health monitoring and diagnosis of rotating machines

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  • Wu, Zhe
  • Zhang, Qiang
  • Cheng, Lifeng
  • Hou, Shuyong
  • Tan, Shengyue

Abstract

It is a challenging task to perform the non-linear system state recognition and safety monitoring under strong noise and complex excitation, to tackle this problem, we innovatively propose the variational mode decomposition multiscale holographic transfer entropy statistics (VMTES) method based on the energy transfer relationship between non-linear system signals. The VMTES is a method that measures the information flow direction and coupling degree between non-linear systems, which can precisely measure the slight changes of energy transfer of a mechanical system, accurately assess the slight mutation of dynamical behaviors and status change of a mechanical system and therefore realize fault location and quantification of the non-linear rotating machinery system. The damage severity and direction of the measure point can be precisely described with the VMTES damage assessment indicator, providing the reliable basis for the structural health monitoring and fault diagnosis of the mechanical system. By applying the result to the state recognition of a chaotic system and the structural health monitoring of a rotating machinery system, we can see from the experimental results that the VMTES can effectively detect the fault of gears and rolling bearings under several working conditions. Based on the experiment, we also explain how this method simultaneously locate and quantify the non-linear vibration caused by the fault.

Suggested Citation

  • Wu, Zhe & Zhang, Qiang & Cheng, Lifeng & Hou, Shuyong & Tan, Shengyue, 2020. "The VMTES: Application to the structural health monitoring and diagnosis of rotating machines," Renewable Energy, Elsevier, vol. 162(C), pages 2380-2396.
    • Handle: RePEc:eee:renene:v:162:y:2020:i:c:p:2380-2396
    DOI: 10.1016/j.renene.2020.10.021
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    References listed on IDEAS

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    1. Kong, Yun & Wang, Tianyang & Chu, Fulei, 2019. "Meshing frequency modulation assisted empirical wavelet transform for fault diagnosis of wind turbine planetary ring gear," Renewable Energy, Elsevier, vol. 132(C), pages 1373-1388.
    2. Feng, Zhipeng & Liang, Ming & Zhang, Yi & Hou, Shumin, 2012. "Fault diagnosis for wind turbine planetary gearboxes via demodulation analysis based on ensemble empirical mode decomposition and energy separation," Renewable Energy, Elsevier, vol. 47(C), pages 112-126.
    3. Teng, Wei & Ding, Xian & Cheng, Hao & Han, Chen & Liu, Yibing & Mu, Haihua, 2019. "Compound faults diagnosis and analysis for a wind turbine gearbox via a novel vibration model and empirical wavelet transform," Renewable Energy, Elsevier, vol. 136(C), pages 393-402.
    4. Dimpfl Thomas & Peter Franziska Julia, 2013. "Using transfer entropy to measure information flows between financial markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 85-102, February.
    5. J. T. Lizier & M. Prokopenko, 2010. "Differentiating information transfer and causal effect," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(4), pages 605-615, February.
    6. Martinez-Luengo, Maria & Kolios, Athanasios & Wang, Lin, 2016. "Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 91-105.
    7. Alessandro Montalto & Luca Faes & Daniele Marinazzo, 2014. "MuTE: A MATLAB Toolbox to Compare Established and Novel Estimators of the Multivariate Transfer Entropy," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.
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