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Non-Contact Wind Turbine Blade Crack Detection Using Laser Doppler Vibrometers

Author

Listed:
  • Ali Zabihi

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA)

  • Farhood Aghdasi

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA)

  • Chadi Ellouzi

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA)

  • Nand Kishore Singh

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA)

  • Ratneshwar Jha

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA
    Aerospace, Physics, and Space Sciences, Florida Institute of Technology, Melbourne, FL 08028, USA)

  • Chen Shen

    (Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA)

Abstract

In response to the growing global demand for both energy and a clean environment, there has been an unprecedented rise in the utilization of renewable energy. Wind energy plays a crucial role in striving for carbon neutrality due to its eco-friendly characteristics. Despite its significance, wind energy infrastructure is susceptible to damage from various factors including wind or sea waves, rapidly changing environmental conditions, delamination, crack formation, and structural deterioration over time. This research focuses on investigating non-destructive testing (NDT) of wind turbine blades (WTBs) using approaches based on the vibration of the structures. To this end, WTBs are first made from glass fiber-reinforcement polymer (GFRP) using composite molding techniques, and then a short pulse is generated in the structure by a piezoelectric actuator made from lead zirconate titanate (PZT-5H) to generate guided waves. A numerical approach is presented based on solving the elastic time-harmonic wave equations, and a laser Doppler vibrometer (LDV) is utilized to collect the vibrational data in a remote manner, thereby facilitating the crack detection of WTBs. Subsequently, the wave propagation characteristics of intact and damaged structures are analyzed using the Hilbert–Huang transformation (HHT) and fast Fourier transformation (FFT). The results reveal noteworthy distinctions in damaged structures, where the frequency domain exhibits additional components beyond those identified by FFT, and the time domain displays irregularities in proximity to the crack region, as detected by HHT. The results suggest a feasible approach to detecting potential cracks of WTBs in a non-contact and reliable way.

Suggested Citation

  • Ali Zabihi & Farhood Aghdasi & Chadi Ellouzi & Nand Kishore Singh & Ratneshwar Jha & Chen Shen, 2024. "Non-Contact Wind Turbine Blade Crack Detection Using Laser Doppler Vibrometers," Energies, MDPI, vol. 17(9), pages 1-14, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2165-:d:1387314
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    References listed on IDEAS

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    1. Bo Chen & Sheng-lin Zhao & Peng-yun Li, 2014. "Application of Hilbert-Huang Transform in Structural Health Monitoring: A State-of-the-Art Review," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-22, June.
    2. Amna Algolfat & Weizhuo Wang & Alhussein Albarbar, 2023. "The Sensitivity of 5MW Wind Turbine Blade Sections to the Existence of Damage," Energies, MDPI, vol. 16(3), pages 1-20, January.
    3. Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Condition monitoring of wind turbine blades based on self-supervised health representation learning: A conducive technique to effective and reliable utilization of wind energy," Applied Energy, Elsevier, vol. 313(C).
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