{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:18:31Z","timestamp":1776399511864,"version":"3.51.2"},"reference-count":22,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenzhen Science and Technology Programe","award":["GJHZ20210705142538004"],"award-info":[{"award-number":["GJHZ20210705142538004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 \u03c0-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.<\/jats:p>","DOI":"10.3390\/s23187821","type":"journal-article","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T21:41:12Z","timestamp":1694554872000},"page":"7821","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["\u03c0-FBG Fiber Optic Acoustic Emission Sensor for the Crack Detection of Wind Turbine Blades"],"prefix":"10.3390","volume":"23","author":[{"given":"Qi","family":"Yan","sequence":"first","affiliation":[{"name":"School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China"}]},{"given":"Xingchen","family":"Che","sequence":"additional","affiliation":[{"name":"School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China"}]},{"given":"Shen","family":"Li","sequence":"additional","affiliation":[{"name":"School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China"}]},{"given":"Gensheng","family":"Wang","sequence":"additional","affiliation":[{"name":"SPIC Jiangxi Electric Power Co., Ltd., Nanchang 330096, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8898-8898","authenticated-orcid":false,"given":"Xiaoying","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China"},{"name":"Technology Research Institute, Shenzhen Huazhong University of Science, Shenzhen 518057, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"ref_1","unstructured":"Global Wind Energy Council (2021). GWEC|Global Wind Report 2021, Global Wind Energy Council."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1109\/TEC.2006.889614","article-title":"Survey of failures in wind power systems with focus on Swedish wind power plants during 1997\u20132005","volume":"22","author":"Ribrant","year":"2007","journal-title":"IEEE Trans. Energy Convers"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"21020","DOI":"10.1109\/ACCESS.2018.2818678","article-title":"A data-driven design for fault detection ofwind turbines using random forests and XGBoost","volume":"6","author":"Zhang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.renene.2012.03.003","article-title":"Condition monitoring of wind turbines: Techniques and methods","volume":"46","author":"Tobias","year":"2012","journal-title":"Renew. Energy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1016\/j.engfailanal.2008.02.005","article-title":"Study of fatigue damage in wind turbine blades","volume":"16","author":"Barroso","year":"2009","journal-title":"Eng. Fail. Anal."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1109\/TMECH.2019.2908233","article-title":"A two-stage data-driven approach for image-basedwind turbine blade crack inspections","volume":"24","author":"Wang","year":"2019","journal-title":"IEEE ASME Trans. Mechatron."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.renene.2012.08.072","article-title":"Review of structural health and cure monitoring techniques for large wind turbine blades","volume":"51","author":"Schubel","year":"2013","journal-title":"Renew. Energy"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.ymssp.2016.05.011","article-title":"Feasibility study on a strain based deflection monitoring system for wind turbine blades","volume":"82","author":"Lee","year":"2017","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2198","DOI":"10.1016\/j.ymssp.2006.10.002","article-title":"Development in vibration-based structural damage detection technique","volume":"21","author":"Yan","year":"2007","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1833","DOI":"10.1016\/j.jsv.2013.11.015","article-title":"On damage diagnosis for a wind turbine blade using pattern recognition","volume":"333","author":"Dervilis","year":"2014","journal-title":"J. Sound Vib."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Stokkeland, M., Klausen, K., and Johansen, T.A. (2015, January 9\u201312). Autonomous visual navigation of unmanned aerial vehicle for wind turbine inspection. Proceedings of the International Conference on Materials for Renewable Energy & Environment, Denver, CO, USA.","DOI":"10.1109\/ICUAS.2015.7152389"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1704","DOI":"10.1016\/j.engstruct.2010.02.020","article-title":"Acoustic emission monitoring of bridges: Review and case studies","volume":"32","author":"Nair","year":"2010","journal-title":"Eng. Struct."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"139695","DOI":"10.1155\/2015\/139695","article-title":"Moore: Structural health monitoring of wind turbine blades: Acoustic source localization using wireless sensor networks","volume":"2015","author":"Bouzid","year":"2015","journal-title":"J. Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1049\/iet-rpg.2016.0087","article-title":"Structural health monitoring of composite wind turbine blades: Challenges, issues and potential solutions","volume":"11","author":"Yang","year":"2017","journal-title":"IET Renew. Power Gener."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.prostr.2016.02.008","article-title":"A review of non-destructive testing methods of composite materials","volume":"1","author":"Gholizadeh","year":"2016","journal-title":"Procedia Struct. Integr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Jinachandran, S., and Rajan, G. (2021). Fibre Bragg Grating Based Acoustic Emission Measurement System for Structural Health Monitoring Applications. Materials, 14.","DOI":"10.3390\/ma14040897"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1117\/12.435542","article-title":"Acoustic emission detection using fiber Bragg gratings","volume":"4328","author":"Perze","year":"2001","journal-title":"Proc. SPIE"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4473","DOI":"10.1109\/JLT.2016.2587161","article-title":"Fiber Bragg grating\u2043based cascaded acoustic sensors for potential marine structural condition monitoring","volume":"34","author":"Vidakovic","year":"2016","journal-title":"J. Light. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1007\/s42452-021-04650-0","article-title":"Optimal parameters for fiber Bragg gratings for sensing applications: A spectral study","volume":"3","author":"Shekar","year":"2021","journal-title":"SN Appl. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.ijleo.2015.09.067","article-title":"Multi-source acoustic emission localization technology research based on FBG sensing network and time reversal focusing imaging","volume":"127","author":"Sai","year":"2016","journal-title":"Optik"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.neucom.2012.11.012","article-title":"Fault diagnosis of rolling element bearing using cyclic autocorrelation and wavelet transform","volume":"110","author":"Sharma","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/18\/7821\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:49:21Z","timestamp":1760129361000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/18\/7821"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,12]]},"references-count":22,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["s23187821"],"URL":"https:\/\/doi.org\/10.3390\/s23187821","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,12]]}}}