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AI for Wind Turbine contaminant removal

2023-11-28 | Digital for Decarbonization
  • Contaminants on wind turbine blades, whether organic (insects, birds, plant matter) or inorganic (soil, sand, salt), can negatively impact turbine performance.

  • Standoff laser ablation and LIBS in the vacuum ultraviolet (VUV) and ultraviolet visible (UV-Vis) spectral ranges were employed to investigate and detect contamination on wind turbine blades.

  • Study found that SVM performed the best among the tested ML algorithms, followed by PLS-DA, CNN, and CL. SVM demonstrated high accuracy and precision, making the LIBS spectra linearly separable when projected via principal component analysis (PCA).

  • Impact: AI has better chances of control for contaminants clear, and is way efficient.