Data-Driven Diagnosis of Nonlinearly Mixed Mechanical Faults in Wind Turbine Gearbox

This letter proposes an efficient algorithmic solution to diagnose multiple mechanical faults in wind turbine gearbox through source number estimation using an empirical mode decomposition (EMD) and singular value decomposition (SVD) joint approach, and source signal recovery based on short-time Fourier transform (STFT), fuzzy <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {C}$ </tex-math></inline-formula>-means clustering and <inline-formula> <tex-math notation="LaTeX">$\boldsymbol {l_{1}}$ </tex-math></inline-formula> norm decomposition. The effectiveness of the solution is validated using real wind turbine measurements under multifault scenarios.