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Prediction of hydroelectric turbine runner strain signal via cyclostationary decomposition and kriging interpolation

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  • Pham, Quang Hung
  • Gagnon, Martin
  • Antoni, Jérôme
  • Tahan, Antoine
  • Monette, Christine

Abstract

Strain measurements by gauges can play an important role in analyzing the fatigue damage of the hydroelectric turbine runner. However, these measurements cannot cover every steady-state operating condition due to the experimental limitations. Thus, the aim of this research is to predict the strain signal on runner over every possible steady operating condition using available experimental measurements. The strain signal measured during steady state involves several components (such as periodicity, vortex rope component and stochastic components) which can generate difficulties during the prediction. This paper proposes a solution to predict the runner strain signals by independently interpolating each physical phenomenon over different turbine operating conditions. These components are extracted using cyclostationary decomposition operators. A case study is performed on a Francis hydroelectric turbine to verify the interpolation performance. The proposed methodology can contribute to the fatigue assessment and help to reduce the requirements of infield measurements.

Suggested Citation

  • Pham, Quang Hung & Gagnon, Martin & Antoni, Jérôme & Tahan, Antoine & Monette, Christine, 2022. "Prediction of hydroelectric turbine runner strain signal via cyclostationary decomposition and kriging interpolation," Renewable Energy, Elsevier, vol. 182(C), pages 998-1011.
    • Handle: RePEc:eee:renene:v:182:y:2022:i:c:p:998-1011
    DOI: 10.1016/j.renene.2021.11.017
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    References listed on IDEAS

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    1. Pham, Quang Hung & Gagnon, Martin & Antoni, Jérôme & Tahan, Antoine & Monette, Christine, 2021. "Rainflow-counting matrix interpolation over different operating conditions for hydroelectric turbine fatigue assessment," Renewable Energy, Elsevier, vol. 172(C), pages 465-476.
    2. Liu, Xin & Luo, Yongyao & Wang, Zhengwei, 2016. "A review on fatigue damage mechanism in hydro turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1-14.
    3. Presas, Alexandre & Luo, Yongyao & Wang, Zhengwei & Guo, Bao, 2019. "Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 96-110.
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    Cited by:

    1. Wang, Huan & Li, Wenfeng & Hou, Yaochun & Wu, Peng & Huang, Bin & Wu, Kelin & Wu, Dazhuan, 2023. "Recognition of the developing vortex rope in Francis turbine draft tube based on PSO-CS2," Renewable Energy, Elsevier, vol. 217(C).
    2. Shande Li & Shuai Yuan & Shaowei Liu & Jian Wen & Qibai Huang, 2022. "Research on an Accuracy Optimization Algorithm of Kriging Model Based on a Multipoint Filling Criterion," Mathematics, MDPI, vol. 10(9), pages 1-11, May.

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