{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T15:12:47Z","timestamp":1773155567466,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,23]],"date-time":"2022-10-23T00:00:00Z","timestamp":1666483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52078084"],"award-info":[{"award-number":["52078084"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022CDJKYJH032"],"award-info":[{"award-number":["2022CDJKYJH032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["cstc2021jcyj-msxmX0623"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0623"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["52078084"],"award-info":[{"award-number":["52078084"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2022CDJKYJH032"],"award-info":[{"award-number":["2022CDJKYJH032"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["cstc2021jcyj-msxmX0623"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0623"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Natural Science Foundation of Chongqing","award":["52078084"],"award-info":[{"award-number":["52078084"]}]},{"name":"National Natural Science Foundation of Chongqing","award":["2022CDJKYJH032"],"award-info":[{"award-number":["2022CDJKYJH032"]}]},{"name":"National Natural Science Foundation of Chongqing","award":["cstc2021jcyj-msxmX0623"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0623"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The motion information of blades is a key reflection of the operation state of an entire wind turbine unit. However, the special structure and operation characteristics of rotating blades have become critical obstacles for existing contact vibration monitoring technologies. Digital image correlation performs powerfully in non-contact, full-field measurements, and has increasingly become a popular method for solving the problem of rotating blade monitoring. Aiming at the problem of large-scale rotation matching for blades, this paper proposes a modified speeded-up robust features (SURF)-enhanced digital image correlation algorithm to extract the full-field deformation of blades. Combining an angle compensation (AC) strategy, the AC-SURF algorithm is developed to estimate the rotation angle. Then, an iterative process is presented to calculate the accurate rotation displacement. Subsequently, with reference to the initial state of rotation, the relative strain distribution caused by flaws is determined. Finally, the sensitivity of the strain is validated by comparing the three damage indicators including unbalanced rotational displacement, frequency change, and surface strain field. The performance of the proposed algorithm is verified by laboratory tests of blade damage detection and wind turbine model deformation monitoring. The study demonstrated that the proposed method provides an effective and robust solution for the operation status monitoring and damage detection of wind turbine blades. Furthermore, the strain-based damage detection algorithm is more advantageous in identifying cracks on rotating blades than one based on fluctuated displacement or frequency change.<\/jats:p>","DOI":"10.3390\/s22218110","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"8110","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Damage Detection for Rotating Blades Using Digital Image Correlation with an AC-SURF Matching Algorithm"],"prefix":"10.3390","volume":"22","author":[{"given":"Jiawei","family":"Gu","sequence":"first","affiliation":[{"name":"School of Civil Engineering, Chongqing University, Chongqing 400045, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2506-0339","authenticated-orcid":false,"given":"Gang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Chongqing University, Chongqing 400045, China"},{"name":"The Key Laboratory of New Technology for Construction of Cities in Mountain Area of the Ministry of Education, Chongqing University, Chongqing 400045, China"}]},{"given":"Mengzhu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Chongqing University, Chongqing 400045, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"18229","DOI":"10.3390\/s150818229","article-title":"In-Situ Cure Monitoring of Wind Turbine Blades by Using Fiber Bragg Grating Sensors and Fresnel Reflection Measurement","volume":"15","author":"Sampath","year":"2015","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"106445","DOI":"10.1016\/j.ymssp.2019.106445","article-title":"Damage detection techniques for wind turbine blades: A review","volume":"141","author":"Du","year":"2020","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Loss, T., and Bergmann, A. (2020). Moving Accelerometers to the Tip: Monitoring of Wind Turbine Blade Bending Using 3D Accelerometers and Model-Based Bending Shapes. Sensors, 20.","DOI":"10.3390\/s20185337"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.optlaseng.2014.04.020","article-title":"Determination of three-dimensional movement for rotary blades using digital image correlation","volume":"65","author":"Wu","year":"2015","journal-title":"Opt. Lasers Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7312","DOI":"10.3390\/s140407312","article-title":"Quantitative Damage Detection and Sparse Sensor Array Optimization of Carbon Fiber Reinforced Resin Composite Laminates for Wind Turbine Blade Structural Health Monitoring","volume":"14","author":"Li","year":"2014","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Civera, M., and Surace, C. (2022). Non-Destructive Techniques for the Condition and Structural Health Monitoring of Wind Turbines: A Literature Review of the Last 20 Years. Sensors, 22.","DOI":"10.3390\/s22041627"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Natili, F., Castellani, F., Astolfi, D., and Becchetti, M. (2020). Video-Tachometer Methodology for Wind Turbine Rotor Speed Measurement. Sensors, 20.","DOI":"10.3390\/s20247314"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1016\/j.renene.2020.04.096","article-title":"Acoustical damage detection of wind turbine blade using the improved incremental support vector data description","volume":"156","author":"Chen","year":"2020","journal-title":"Renew. Energy"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1016\/j.compstruct.2018.06.065","article-title":"Piezoelectric smart composite blades for collision monitoring: Measurement of mechanical properties and impact sensitivity","volume":"202","author":"Kang","year":"2018","journal-title":"Compos. Struct."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1177\/1475921717722725","article-title":"Active vibration-based structural health monitoring system for wind turbine blade: Demonstration on an operating Vestas V27 wind turbine","volume":"16","author":"Tcherniak","year":"2017","journal-title":"Struct. Health Monit. Int. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.compstruct.2015.08.137","article-title":"Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison","volume":"135","year":"2016","journal-title":"Compos. Struct."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1016\/j.renene.2021.10.024","article-title":"Fault diagnosis of wind turbine bearing using a multi-scale convolutional neural network with bidirectional long short term memory and weighted majority voting for multi-sensors","volume":"182","author":"Xu","year":"2022","journal-title":"Renew. Energy"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zhang, C., Yang, T., and Yang, J. (2022). Image Recognition of Wind Turbine Blade Defects Using Attention-Based MobileNetv1-YOLOv4 and Transfer Learning. Sensors, 22.","DOI":"10.3390\/s22166009"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lich, J., Wollmann, T., Filippatos, A., Gude, M., Czarske, J., and Kuschmierz, R. (2021). Spatially Resolved Experimental Modal Analysis on High-Speed Composite Rotors Using a Non-Contact, Non-Rotating Sensor. Sensors, 21.","DOI":"10.3390\/s21144705"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Tian, G.Y., Gao, Y., Li, K., Wang, Y., Gao, B., and He, Y. (2016). Eddy Current Pulsed Thermography with Different Excitation Configurations for Metallic Material and Defect Characterization. Sensors, 16.","DOI":"10.3390\/s16060843"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.optlaseng.2016.10.022","article-title":"Application of scanning laser Doppler vibrometry for delamination detection in composite structures","volume":"99","author":"Kudela","year":"2017","journal-title":"Opt. Lasers Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.ymssp.2016.07.021","article-title":"Large-area photogrammetry based testing of wind turbine blades","volume":"86","author":"Poozesh","year":"2017","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"033001","DOI":"10.1088\/0964-1726\/24\/3\/033001","article-title":"A review of damage detection methods for wind turbine blades","volume":"24","author":"Li","year":"2015","journal-title":"Smart Mater. Struct."},{"key":"ref_19","unstructured":"Scislo, L., and Guinchard, M. (2019, January 7\u201311). Non-invasive measurements of ultra-ligtweight composite materials using laser doppler vibrometry system. Proceedings of the 26 th International Congress on Sound and Vibration, Montreal, QC, Canada."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chen, Y., Escalera Mendoza, A.S., and Griffith, D.T. (2022). Experimental Dynamic Characterization of Both Surfaces of Structures using 3D Scanning Laser Doppler Vibrometer. Experimental Techniques. Exp. Tech., 1\u201318.","DOI":"10.1007\/s40799-022-00604-2"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"116797","DOI":"10.1016\/j.jsv.2022.116797","article-title":"Operational modal analysis of a rotating structure using image-based tracking continuously scanning laser Doppler vibrometry via a novel edge detection method","volume":"525","author":"Lyu","year":"2022","journal-title":"J. Sound Vib."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.rser.2016.05.083","article-title":"Structural health management utilization for lifetime prognosis and advanced control strategy deployment of wind turbines: An overview and outlook concerning actual methods, tools, and obtained results","volume":"64","author":"Beganovic","year":"2016","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"108797","DOI":"10.1016\/j.ymssp.2021.108797","article-title":"Non-uniform illumination image enhancement for surface damage detection of wind turbine blades","volume":"170","author":"Peng","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"108418","DOI":"10.1016\/j.ymssp.2021.108418","article-title":"Structural motion estimation via Hilbert transform enhanced phase-based video processing","volume":"166","author":"Liu","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4802","DOI":"10.1016\/j.energy.2010.09.008","article-title":"Feasibility of monitoring large wind turbines using photogrammetry","volume":"35","author":"Ozbek","year":"2010","journal-title":"Energy"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.jsv.2015.04.026","article-title":"Extracting full-field dynamic strain on a wind turbine rotor subjected to arbitrary excitations using 3D point tracking and a modal expansion technique","volume":"352","author":"Baqersad","year":"2015","journal-title":"J. Sound Vib."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.measurement.2019.03.024","article-title":"Full-field strain prediction using mode shapes measured with digital image correlation","volume":"139","author":"Bharadwaj","year":"2019","journal-title":"Measurement"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.ymssp.2019.05.031","article-title":"Health monitoring of wind turbine blades in operation using three-dimensional digital image correlation","volume":"130","author":"Wu","year":"2019","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1177\/1475921713506766","article-title":"Damage detection and full surface characterization of a wind turbine blade using three-dimensional digital image correlation","volume":"12","author":"LeBlanc","year":"2013","journal-title":"Struct. Health Monit."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.ress.2018.03.014","article-title":"Detection of local bonding failure damage by Digital Image Correlation technique","volume":"184","author":"Huh","year":"2019","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Liu, G., Li, M., Zhang, W., and Gu, J. (2021). Subpixel Matching Using Double-Precision Gradient-Based Method for Digital Image Correlation. Sensors, 21.","DOI":"10.3390\/s21093140"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"106697","DOI":"10.1016\/j.optlaseng.2021.106697","article-title":"Full-field motion and deformation measurement of high speed rotation based on temporal phase-locking and 3D-DIC","volume":"146","author":"Ye","year":"2021","journal-title":"Opt. Lasers Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/j.optlaseng.2011.10.005","article-title":"Initial guess by improved population-based intelligent algorithms for large inter-frame deformation measurement using digital image correlation","volume":"50","author":"Zhao","year":"2012","journal-title":"Opt. Lasers Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"105201","DOI":"10.1088\/1361-6501\/ac7a06","article-title":"A prediction\u2013correction method for fast and accurate initial displacement field estimation in digital image correlation","volume":"33","author":"Yang","year":"2022","journal-title":"Meas. Sci. Technol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.optlaseng.2014.05.013","article-title":"High-efficiency and high-accuracy digital image correlation for three-dimensional measurement","volume":"65","author":"Gao","year":"2015","journal-title":"Opt. Lasers Eng."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1016\/j.optlaseng.2012.06.017","article-title":"Propagation function for accurate initialization and efficiency enhancement of digital image correlation","volume":"50","author":"Zhou","year":"2012","journal-title":"Opt. Lasers Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"107999","DOI":"10.1016\/j.ress.2021.107999","article-title":"Improvement to the discretized initial condition of the generalized density evolution equation","volume":"216","author":"Liu","year":"2021","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Gillich, G.-R., Maia, N.M.M., Wahab, M.A., Tufisi, C., Korka, Z.I., Gillich, N., and Pop, M.V. (2021). Damage Detection on a Beam with Multiple Cracks: A Simplified Method Based on Relative Frequency Shifts. Sensors, 21.","DOI":"10.20944\/preprints202107.0240.v1"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.ymssp.2019.04.002","article-title":"Mode shape identification based on Gabor transform and singular value decomposition under uncorrelated colored noise excitation","volume":"128","author":"Luo","year":"2019","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Yu, W., Liu, Z., Zhuang, Z., Liu, Y., Wang, X., Yang, Y., and Gou, B. (2022). Super-Resolution Reconstruction of Speckle Images of Engineered Bamboo Based on an Attention-Dense Residual Network. Sensors, 22.","DOI":"10.3390\/s22176693"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"108890","DOI":"10.1016\/j.ymssp.2022.108890","article-title":"Vibration-based damage identification in composite plates using 3D-DIC and wavelet analysis","volume":"173","author":"Sun","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"106446","DOI":"10.1016\/j.ymssp.2019.106446","article-title":"Non-contact vibration monitoring of rotating wind turbines using a semi-autonomous UAV","volume":"138","author":"Khadka","year":"2020","journal-title":"Mech. Syst. Signal Process."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8110\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:01:10Z","timestamp":1760144470000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8110"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,23]]},"references-count":42,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["s22218110"],"URL":"https:\/\/doi.org\/10.3390\/s22218110","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,23]]}}}