Lidar-Based Spatial Large Deflection Measurement System for Wind Turbine Blades

被引:2
|
作者
Hu, Yue [1 ]
Zhu, Yutian [1 ]
Zhou, Aiguo [1 ]
Liu, Penghui [2 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai 201804, Peoples R China
[2] Zhuzhou Times New Mat Technol Co Ltd, Zhuzhou 412007, Peoples R China
来源
OPTICS | 2024年 / 5卷 / 01期
关键词
wind turbine blades; three-dimensional deflection measurement; LiDAR distance measurement technology; point cloud registration; DBSCAN clustering; spatial line clustering;
D O I
10.3390/opt5010011
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
With the advancement of China's wind power industry, research into full-scale structural testing of wind turbine blades, including static testing and fatigue testing, has shown increasing significance. Static testing measures the deflection at fixed points, using pull-wire sensors in industrial practice. However, the demerits of this method involve single dimension, excessive deviation, costly experiment, and complex installment. Given the advantages that lidar provides, correspondingly, high data density, precision, and convenience, we proposed a simple and efficient spatial large deflection measurement system for wind turbine blades with multi lidars. For point clouds collected from lidar scanners, registration based on point primitives and geometric primitives, dynamic radius DBSCAN clustering, spatial line clustering, and line integrals are applied to calculate the 3D coordinates of measured points on the blade. Experimentally validated, the proposed method demonstrates its effectiveness in serving as a viable alternative to the traditional pull-wire sensor measurement approach. In the minimum oscillation direction test, the measurement error is controlled within 3% compared to the theoretical value. Simultaneously, in the maximum swing direction test, the 3D coordinates of the measured point remain consistent with the changing trend observed under small deformation. These results confirm the feasibility of the system and its potentials to be generalized.
引用
收藏
页码:151 / 164
页数:14
相关论文
共 50 条
  • [41] Lidar-based Research and Innovation at DTU Wind Energy - a Review
    Mikkelsen, T.
    SCIENCE OF MAKING TORQUE FROM WIND 2014 (TORQUE 2014), 2014, 524
  • [42] Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades
    Barber, Sarah
    Deparday, Julien
    Marykovskiy, Yuriy
    Chatzi, Eleni
    Abdallah, Imad
    Duthe, Gregory
    Magno, Michele
    Polonelli, Tommaso
    Fischer, Raphael
    Muller, Hanna
    WIND ENERGY SCIENCE, 2022, 7 (04) : 1383 - 1398
  • [43] Review of Structural Health Monitoring of Wind Turbine Blades Based on Vibration and Acoustic Measurement
    Sun S.
    Wang T.
    Chu F.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2024, 60 (07): : 79 - 92
  • [44] Investigation of flutter for large, highly flexible wind turbine blades
    Kelley, C. L.
    Paquette, J.
    SCIENCE OF MAKING TORQUE FROM WIND (TORQUE 2020), PTS 1-5, 2020, 1618
  • [45] Electrostatic Shock Risks in Assembly of large Wind Turbine Blades
    Thuermer, Joerg
    Smallwood, Jeremy
    2016 38TH ELECTRICAL OVERSTRESS/ELECTROSTATIC DISCHARGE SYMPOSIUM (EOS/ESD), 2016,
  • [46] Modal Analysis of Three Rotating Blades of Large Wind Turbine
    Hu, Guoyu
    Sun, Wenlei
    Wu, An
    Xu, Yan
    MECHATRONICS AND APPLIED MECHANICS, PTS 1 AND 2, 2012, 157-158 : 697 - 701
  • [47] Airfoil family design for large offshore wind turbine blades
    Mendez, B.
    Munduate, X.
    San Miguel, U.
    SCIENCE OF MAKING TORQUE FROM WIND 2014 (TORQUE 2014), 2014, 524
  • [48] Preliminary design procedure for large wind turbine blades based on the classical lamination theory
    Lee, Sang-Lae
    Shin, SangJoon
    ADVANCED COMPOSITE MATERIALS, 2021, 30 (02) : 131 - 148
  • [49] Innovative design approaches for article large wind turbine blades
    Jackson, KJ
    Zuteck, MD
    van Dam, CP
    Standish, KJ
    Berry, D
    WIND ENERGY, 2005, 8 (02) : 141 - 171
  • [50] AEROELASTIC RESPONSE ANALYSIS OF LARGE FLEXIBLE WIND TURBINE BLADES
    Gao, Long
    Lin, Lihui
    Yang, Wansheng
    Gao, Erjie
    Zhu, Lei
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (08): : 572 - 580