Damage identification of wind turbine blades using continuous wavelet transform: a comprehensive study

Wind turbine blades (WTBs) are critical components that confront complex dynamic loads and environmental effects. Among the common approaches for damage detection, the Continuous Wavelet Transform (CWT)-based methods are widely used. However, the application for complex geometries like WTBs is still limited. The current research papers on the 1D-CWT have no broad aspects regarding damage conditions, and the research on 2D-CWT is still incomplete. Therefore, this paper provides a comprehensive study on the CWT-based methods applied to WTBs, including proposing detection thresholds based on damage sizes. This research is divided into two steps based on damage severity: major and minor. First, the severe damages are modelled to reflect the effect of structural dynamics, emphasising apparent differences from minor damages. The wavelet-based methods with major damage cases are analysed under many parameters, such as wavelet functions, mode orders, damage locations, damage severity, and the number of damages. The obtained optimal parameters are set as a benchmark for detecting minor defects. Moreover, the wavelet comparison between blades, beams, and plates is conducted. Next, the CWT-based methods with minor damage scenarios are analysed to investigate the detection thresholds. The results establish robust and comprehensive recommendations for damage identification of WTBs using CWT.