Broadband Local Spectral Amplitude Analysis for Laser Ultrasonic Imaging of Deep-Seated Defects in Thick-Walled Regions of Wind Turbine Blades

Damage detection in wind turbine blades is crucial for ensuring the safe operation of wind power systems. This article presents a broadband local spectral amplitude analysis method for characterizing hidden damage in the thick-walled regions of wind turbine blades. The proposed method analyzes the enhanced characteristics of the frequency spectrum within specific frequency bands resulting from the interaction between longitudinal waves and damage. First, Fourier transform is applied to the time-space function to obtain the frequency-space spectral function. Subsequently, short-space Fourier transform (SSFT) is used to focus on the amplitude features within specific local regions of the frequency-space spectral function. By extracting the amplitude differences between healthy and damaged regions, 2-D visualization of the hidden damage could be achieved. Following this, average fusion is performed within selected frequency bands to enhance the clarity and noise resistance of the imaging results. The detection scheme employs a noncontact technique combining laser excitation with a laser Doppler vibrometer (LDV) for reception, thereby avoiding issues related to sensor coupling inherent in traditional contact-based detection methods. Experimental results demonstrate that the method can accurately locate the damage center, delineate the damage contours, and exhibit excellent sensitivity and stability in detecting hidden damage at different depths.