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Baseline model based structural health monitoring method under varying environment

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  • Zhao, Xueyan
  • Lang, Ziqiang

Abstract

Environment has significant impacts on the structure performance and will change features of sensor measurements on the monitored structure. The effect of varying environment needs to be considered and eliminated while conducting structural health monitoring. In order to achieve this purpose, a baseline model based structural health monitoring method is proposed in this paper. The relationship between signal features and varying environment, known as a baseline model, is first established. Then, a tolerance range of the signal feature is evaluated via a data based statistical analysis. Furthermore, the health indicator, which is defined as the proportion of signal features within the tolerance range, is used to judge whether the structural system is in normal working condition or not so as to implement the structural health monitoring. Finally, experimental data analysis for an operating wind turbine is conducted and the results demonstrate the performance of the proposed new technique.

Suggested Citation

  • Zhao, Xueyan & Lang, Ziqiang, 2019. "Baseline model based structural health monitoring method under varying environment," Renewable Energy, Elsevier, vol. 138(C), pages 1166-1175.
    • Handle: RePEc:eee:renene:v:138:y:2019:i:c:p:1166-1175
    DOI: 10.1016/j.renene.2019.02.007
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    References listed on IDEAS

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    1. Elforjani, Mohamed & Bechhoefer, Eric, 2018. "Analysis of extremely modulated faulty wind turbine data using spectral kurtosis and signal intensity estimator," Renewable Energy, Elsevier, vol. 127(C), pages 258-268.
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    Cited by:

    1. Hang, Xinyu & Zhu, Xiaoxun & Gao, Xiaoxia & Wang, Yu & Liu, Longhu, 2024. "Study on crack monitoring method of wind turbine blade based on AI model: Integration of classification, detection, segmentation and fault level evaluation," Renewable Energy, Elsevier, vol. 224(C).
    2. Alharthi, Majed & Hanif, Imran & Alamoudi, Hawazen, 2022. "Impact of environmental pollution on human health and financial status of households in MENA countries: Future of using renewable energy to eliminate the environmental pollution," Renewable Energy, Elsevier, vol. 190(C), pages 338-346.
    3. Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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