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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10535792 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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