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Application of Variational Mode Decomposition to Feature Isolation and Diagnosis in a Wind Turbine

  • Qi Zhao
  • Te HanEmail author
  • Dongxiang Jiang
  • Kai Yin
Original Paper
  • 3 Downloads

Abstract

Purpose

In general, when the misalignment fault occurs in a wind turbine, the vibration signals present the non-stationary and non-linear characteristic nature. The early misalignment fault signal is easily overwhelmed by the strong background signals and noise, making it difficult to detect reliable fault feature. This work focuses on the signal processing-based feature Isolation and Diagnosis for misalignment faults.

Methods

In this paper, a novel variational mode decomposition (VMD) is introduced to address the issue instead of other common adaptive decomposition algorithms such as empirical mode decomposition (EMD) and wavelet transform. VMD is capable of decomposing the fault vibration signal into several stable components and realize the separation of misalignment fault component from background signals.

Results

Both the numerical simulation and a case study using the fault data from our test rig demonstrate the effectiveness of this method. The characteristic 2X frequency can be extracted from the stable components obtained by VMD efficiently. On the contrary, the fault feature of the components decomposed by the comparative methods is relatively unconspicuous due to the mode mixing and frequency aliasing.

Keywords

Variational mode decomposition Feature extraction Misalignment fault Wind turbine 

Notes

Acknowledgements

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by the National Natural Science Foundation of China (No. 51174273) and the project of State Key Lab of Power Systems (No. SKLD16Z12).

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Copyright information

© Krishtel eMaging Solutions Private Limited 2019

Authors and Affiliations

  1. 1.AECC Commercial Aircraft Engine Co.,LtdShanghaiChina
  2. 2.State Key Lab of Control and Simulation of Power System and Generation Equipment, Department of Energy and Power EngineeringTsinghua UniversityBeijingChina

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