Feasibility of monitoring large wind turbines using photogrammetry

被引:125
|
作者
Ozbek, Muammer [1 ]
Rixen, Daniel J. [1 ]
Erne, Oliver [2 ]
Sanow, Gunter [2 ]
机构
[1] Delft Univ Technol, Fac Mech Engn, NL-2628 CD Delft, Netherlands
[2] GOM mbH Opt Measuring Tech, D-38106 Braunschweig, Germany
关键词
Wind turbine; Dynamic tests; Vibration measurements; Photogrammetry; Videogrammetry; Optical measurement techniques; IMAGE CORRELATION PHOTOGRAMMETRY; FIELD DYNAMIC DISPLACEMENT; GPS; BLADE; LOAD;
D O I
10.1016/j.energy.2010.09.008
中图分类号
O414.1 [热力学];
学科分类号
摘要
Photogrammetry, which is a proven measurement technique based on determination of the 3D coordinates of the points on an object by using two or more images taken from different positions, is proposed to be a promising and cost efficient alternative for monitoring the dynamic behavior of wind turbines. The pros and cons of utilizing this measurement technique for several applications such as dynamic testing or health monitoring of large wind turbines are discussed by presenting the results of the infield tests performed on a 2.5 MW - 80 m diameter - wind turbine. Within the scope of the work, the 3D dynamic response of the rotor is captured at 33 different locations simultaneously by using 4 CCD (charge coupled device) cameras while the turbine is rotating. Initial results show that the deformations on the turbine can be measured with an average accuracy of 25 mm from a measurement distance of 220 m. Preliminary analyses of the measurements also show that some of the important turbine modes can be identified from photogrammetric measurement data. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4802 / 4811
页数:10
相关论文
共 50 条
  • [11] Operational Condition Monitoring of Wind Turbines Using Cointegration Method
    Dao, Phong B.
    Staszewski, Wieslaw J.
    Uhl, Tadeusz
    ADVANCES IN CONDITION MONITORING OF MACHINERY IN NON-STATIONARY OPERATIONS, CMMNO 2016, 2018, 9
  • [12] Using Bayesian updating for monopile offshore wind turbines monitoring
    Xu, Pengfei
    Chen, Jianyun
    Li, Jing
    Fan, Shuli
    Xu, Qiang
    OCEAN ENGINEERING, 2023, 280
  • [13] Performance monitoring of wind turbines using advanced statistical methods
    Anil Kumar Kushwah
    Rajesh Wadhvani
    Sādhanā, 2019, 44
  • [14] Feasibility of Hydrostatic Transmission in Community Wind Turbines
    Sheng, Yingkun
    Escobar-Naranjo, Daniel
    Stelson, Kim A.
    ACTUATORS, 2023, 12 (11)
  • [15] Structural vibration monitoring of wind turbines
    Mostboeck, A.
    Petryna, Y.
    EURODYN 2014: IX INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS, 2014, : 3643 - 3649
  • [16] Structural health monitoring of wind turbines
    Simmermacher, T
    James, GH
    Hurtado, JE
    STRUCTURAL HEALT H MONITORING: CURRENT STATUS AND PERSPECTIVES, 1997, : 788 - 797
  • [17] In-field monitoring of wind turbines
    Rumsey, M
    Hurtado, J
    Hansche, B
    Simmermacher, T
    Carne, T
    Gross, E
    SOUND AND VIBRATION, 1998, 32 (02): : 14 - 19
  • [18] Strain monitoring of wind turbines using a semi-autonomous drone
    Khadka, Ashim
    Afshar, Arash
    Zadeh, Mehrdad
    Baqersad, Javad
    WIND ENGINEERING, 2022, 46 (01) : 296 - 307
  • [19] Predictive Diagnosis for Offshore Wind Turbines using Holistic Condition Monitoring
    Miguelanez, Emilio
    Lane, David
    OCEANS 2010, 2010,
  • [20] Preventive Maintenance of Wind Turbines Using Remote Instrument Monitoring System
    Krishna, D. Gopi
    2012 IEEE FIFTH POWER INDIA CONFERENCE, 2012,