Modal-Feature-Based Detection of Localized Structural Damage in Large Wind Turbine Blades
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Abstract
Vibration-based prognostics and health management (PHM) of large composite wind turbine blades requires damage-sensitive features that are both globally observable and spatially diagnostic for localized damage. Natural frequencies, the most commonly used vibration indicators, are global by construction and may be insensitive to localized stiffness changes in large composite structures. Higher-order mode-shape derivatives offer theoretical advantages, but they have not been systematically compared on a reference-scale composite blade under controlled damage parametrization. This dissertation develops a parametric framework that introduces localized stiffness degradation at the composite-layup level and compares natural frequencies, mode shapes, and their spatial derivatives across a structured matrix of damage cases. Preliminary results show that frequency shifts remain below 1% for most mode–case combinations involving spatially localized stiffness degradation, while curvature-based indicators provide the strongest spatial signatures only in specific mode-and-component combinations. Selected curvature signatures also remain stable under the single rated-speed rotating condition examined. The remaining program expands the damage matrix, refines the derivative-extraction step, and cross-validates the beam-level results against shell-element models. The resulting features will then be evaluated as candidate inputs for prognostic modeling.
How to Cite
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Wind turbine blade, Structural health monitoring, Localized damage, Modal analysis, Mode shape curvature
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