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π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades

Wind power is growing rapidly as a green and clean energy source. As the core part of a wind turbine, the blades are subjected to enormous stress in harsh environments over a long period of time and are therefore extremely susceptible to damage, while at the same time, they are costly, so it is impo...

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Detalles Bibliográficos
Autores principales: Yan, Qi, Che, Xingchen, Li, Shen, Wang, Gensheng, Liu, Xiaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535792/
https://www.ncbi.nlm.nih.gov/pubmed/37765878
http://dx.doi.org/10.3390/s23187821
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author Yan, Qi
Che, Xingchen
Li, Shen
Wang, Gensheng
Liu, Xiaoying
author_facet Yan, Qi
Che, Xingchen
Li, Shen
Wang, Gensheng
Liu, Xiaoying
author_sort Yan, Qi
collection PubMed
description Wind power is growing rapidly as a green and clean energy source. As the core part of a wind turbine, the blades are subjected to enormous stress in harsh environments over a long period of time and are therefore extremely susceptible to damage, while at the same time, they are costly, so it is important to monitor their damage in a timely manner. This paper is based on the detection of blade damage using acoustic emission signals, which can detect early minor damage and internal damage to the blades. Instead of conventional piezoelectric sensors, we use fiber optic gratings as sensing units, which have the advantage of small size and corrosion resistance. Furthermore, the sensitivity of the system is doubled by replacing the conventional FBG (fiber Bragg grating) with a π-phase-shifted FBG. For the noise problem existing in the system, this paper combines the traditional WPD (wavelet packet decomposition) denoising method with EMD (empirical mode decomposition) to achieve a better noise reduction effect. Finally, small wind turbine blades are used in the experiment and their acoustic emission signals with different damage are collected for feature analysis, which sets the stage for the subsequent detection of different damage degrees and types.
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spelling pubmed-105357922023-09-29 π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades Yan, Qi Che, Xingchen Li, Shen Wang, Gensheng Liu, Xiaoying Sensors (Basel) Article Wind power is growing rapidly as a green and clean energy source. As the core part of a wind turbine, the blades are subjected to enormous stress in harsh environments over a long period of time and are therefore extremely susceptible to damage, while at the same time, they are costly, so it is important to monitor their damage in a timely manner. This paper is based on the detection of blade damage using acoustic emission signals, which can detect early minor damage and internal damage to the blades. Instead of conventional piezoelectric sensors, we use fiber optic gratings as sensing units, which have the advantage of small size and corrosion resistance. Furthermore, the sensitivity of the system is doubled by replacing the conventional FBG (fiber Bragg grating) with a π-phase-shifted FBG. For the noise problem existing in the system, this paper combines the traditional WPD (wavelet packet decomposition) denoising method with EMD (empirical mode decomposition) to achieve a better noise reduction effect. Finally, small wind turbine blades are used in the experiment and their acoustic emission signals with different damage are collected for feature analysis, which sets the stage for the subsequent detection of different damage degrees and types. MDPI 2023-09-12 /pmc/articles/PMC10535792/ /pubmed/37765878 http://dx.doi.org/10.3390/s23187821 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yan, Qi
Che, Xingchen
Li, Shen
Wang, Gensheng
Liu, Xiaoying
π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title_full π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title_fullStr π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title_full_unstemmed π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title_short π-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades
title_sort π-fbg fiber optic acoustic emission sensor for the crack detection of wind turbine blades
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535792/
https://www.ncbi.nlm.nih.gov/pubmed/37765878
http://dx.doi.org/10.3390/s23187821
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