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Improving Hilbert–Huang transform for energy-correlation fluctuation in hydraulic engineering

Shibao Lu, Xiaoling Zhang*, Yizi Shang*, Wei Li, Martin Skitmore, Shuli Jiang, Yangang Xue

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Intense vibrations in hydraulic turbine generator unit draft tubes lead to a run-out of the unit shafting and threaten its safe and stable operation. Correct maintenance is therefore important for the safe operation of such units. This study involves assessing the condition of the turbine generator unit by extracting the feature information of its vibration signals. Based on previous research, we present an enhanced Hilbert–Huang transform (HHT) method with an energy-correlation fluctuation criterion to extract feature information and effectively verify the method with simulated signals. An inspection application based on the signal from a vortex strip in the draft tube of a prototype turbine under suboptimal operating conditions indicates that this method is more effective than the traditional one, with a better component identification capability and better suited to the analysis of the complex and dynamic feature information of hydro turbines.
Original languageEnglish
Pages (from-to)1341-1350
JournalEnergy
Volume164
Online published16 Aug 2018
DOIs
Publication statusPublished - 1 Dec 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • Condition-based maintenance
  • Dynamic feature information
  • False component
  • Hilbert–Huang transform method
  • Vortex strip in draft tube

RGC Funding Information

  • RGC-funded

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