Piezoelectric wave method combined with PIMD for wind turbine blade crack identification

To achieve high-precision identification and quantitative assessment of crack damage in wind turbine blades, this paper proposes a damage detection method that uses piezoelectric wave as the sensing signal and integrates PIMD (Precise Identification Mode Decomposition), an improved algorithm based on traditional EMD. Traditional EMD exhibits inherent limitations in precisely identifying signal extrema points, resulting in severe modal overlap and residual noise that significantly compromises damage detection accuracy. The proposed PIMD fundamentally enhances peak-to-valley localisation accuracy by introducing a precise identification strategy, avoiding feature loss and residual noise caused by noise-assisted filtering. Experiments show that PIMD reduces peak identification error by 42% compared with EMD and achieves clear mode separation under multi-crack damage conditions. The energy variation in IMF1–3 decomposed by PIMD is significantly correlated with damage severity, and the proposed damage index (DI) can effectively quantify crack depth, number, and width. This study provides an effective signal processing and quantitative assessment solution for crack damage detection in wind turbine blades under laboratory conditions.