Application of synchrosqueezed wavelet transforms in Lamb wave based structural health monitoring of wind turbine blades

被引:0
|
作者
Xue, Xinyu [1 ]
Sun, Dabiao [1 ]
Gu, Lei [1 ]
Wang, Qiang [1 ]
机构
[1] Nanjing Univ Posts & Telecommun, Nanjing 210023, Peoples R China
来源
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
关键词
Synchrosqueezed Wavelet Transforms; Lamb Wave; Structural Health Monitoring; Wind Turbine Blade;
D O I
10.1109/ccdc.2019.8832600
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The wind turbines are deployed in harsh natural environments and operate at high loads. In this situation, the wind turbine blades arc easily damaged. Active Lamb wave based structure health monitoring technology is a proper way to ensure the safe operation of wind turbines. However, due to the complex propagation of Lamb waves in the wind turbine blades, it's usually hard to analyze the responses and to extract the characteristic parameters. Synchrosqueezed wavelet transforms is a one of the new time-frequency domain analysis methods. It is based on wavelet transform and synchrosqueezed compression to extract wavelet ridges, which makes the time-frequency expression of harmonic signals clearer. In this paper, the application of synchrosqueezed wavelet transforms are introduced based on the analysis of the mechanism of active Lamb wave based structural health monitoring. In the experiments, wavelet transform and synchrosqueezed wavelet transforms was performed on a series of responses, and the effectiveness of synchrosqueezed wavelet transforms in active Lamb wave based structural health monitoring is verified by comparison.
引用
收藏
页码:3190 / 3195
页数:6
相关论文
共 50 条
  • [31] Structural health monitoring of composite wind turbine blades: challenges, issues and potential solutions
    Yang, Wenxian
    Peng, Zhike
    Wei, Kexiang
    Tian, Wenye
    IET RENEWABLE POWER GENERATION, 2017, 11 (04) : 411 - 416
  • [32] Effective Methods for Structural Health Monitoring of Critical Zones of Scalable Wind Turbine Blades
    Swin, Adriana
    Iftimie, Nicoleta
    Steigmann, Rozina
    Rosu, Donn
    Dobrescu, Gabriel Silviu
    Grum, Janez
    Barsanescu, Paul Doru
    STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 2018, 64 (11): : 680 - 689
  • [33] Structural health monitoring of critical zones of small wind turbine blades for domestic users
    Savin, A.
    Iftimie, N.
    Nastac, S. M.
    Stanciu, M. D.
    INNOVATIVE MANUFACTURING ENGINEERING AND ENERGY (IMANEE 2019) - 50 YEARS OF HIGHER TECHNICAL EDUCATION AT THE UNIVERSITY OF PITESTI, 2019, 564
  • [34] Trend Decomposition for Temperature Compensation in a Radar-Based Structural Health Monitoring System of Wind Turbine Blades
    Simon, Jonas
    Moll, Jochen
    Krozer, Viktor
    SENSORS, 2024, 24 (03)
  • [35] Health monitoring of operating wind turbine blades with acoustic emission
    Tsopelas, N.
    Kourousis, D.
    Ladis, I.
    Anastasopoulos, A.
    Lekou, D. J.
    Mouzakis, F.
    EMERGING TECHNOLOGIES IN NON-DESTRUCTIVE TESTING V, 2012, : 347 - 352
  • [36] Structural health monitoring for delamination detection and location in wind turbine blades employing guided waves
    Gomez Munoz, Carlos Quiterio
    Garcia Marquez, Fausto Pedro
    Crespo, Borja Hernandez
    Makaya, Kena
    WIND ENERGY, 2019, 22 (05) : 698 - 711
  • [37] An experimental investigation into passive acoustic damage detection for structural health monitoring of wind turbine blades
    Solimine, Jaclyn
    Niezrecki, Christopher
    Inalpolat, Murat
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2020, 19 (06): : 1711 - 1725
  • [38] Application of Instantaneous Parameter Characteristic in Active Lamb Wave Based Monitoring of Plate Structural Health
    Xu, Baochun
    Wang, Mulan
    Li, Peijuan
    Cheng, Qihua
    Sheng, Yunlong
    APPLIED SCIENCES-BASEL, 2020, 10 (16):
  • [39] Structural health monitoring of wind turbine blades - art. no. 69330E
    Rumsey, Mark A.
    Paquette, Joshua A.
    SMART SENSOR PHENOMENA, TECHNOLOGY, NETWORKS, AND SYSTEMS 2008, 2008, 6933 : E9330 - E9330
  • [40] Bearing monitoring in the wind turbine drivetrain: A comparative study of the FFT and wavelet transforms
    Strombergsson, Daniel
    Marklund, Par
    Berglund, Kim
    Larsson, Per-Erik
    WIND ENERGY, 2020, 23 (06) : 1381 - 1393