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

Author:

Zabihi Ali1ORCID,Aghdasi Farhood1,Ellouzi Chadi1,Singh Nand Kishore1ORCID,Jha Ratneshwar12,Shen Chen1ORCID

Affiliation:

1. Department of Mechanical Engineering, Rowan University, Glassboro, NJ 08028, USA

2. Aerospace, Physics, and Space Sciences, Florida Institute of Technology, Melbourne, FL 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.

Funder

National Science Foundation

New Jersey Economic Development Authority

Publisher

MDPI AG

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