Abstract
A damage mechanism based approach to the structural health monitoring of wind turbine blades is formulated. Typical physical mechanisms of wind turbine blade degradation, including surface erosion, adhesive fatigue, laminate cracking and in some cases compressive kinking and failure are reviewed. Examples of a local, damage mechanism based approach to the structural health monitoring of wind turbine blades are demonstrated, including the monitoring of leading edge erosion of wind turbine blades, adhesive bond failure, plydrop delamination, static and dynamic plydrop tests, and bolt and laminate fatigue. The examples demonstrate the possibilities of monitoring specific damage mechanisms, and specific localizations of wind turbine blades.
Highlights
205 GW of wind energy capacity is available in Europe
The acoustic emission (AE) technique, based on recording and analyzing acoustic waves generated by a blade material when it becomes damaged, has proven its high effectiveness in identifying damage in wind turbine blades
Li et al [55] proposed fiber-reinforced polymers with an embedded graphene sensing network connected to the guided ultrasonic wave (GUW)-based structural health monitoring (SHM) system
Summary
205 GW of wind energy capacity is available in Europe. By 2030, 323 GW of wind energy will be installed in the EU [1]. The maintenance can be realized as corrective maintenance strategy (i.e., the maintenance and repair activity starts only after a failure or damage event), preventive (time-based) maintenance (i.e., regular inspections of wind turbines, allowing early identification of coming damage or failure). Installing structural health monitoring requires local modification of wind turbine blade materials, leading to additional costs and efforts. The idea of the damage mechanism based (mechanism-informed) structural health monitoring of wind turbine blades is formulated. Damage mechanism based approach to the structural health monitoring of wind turbine. The examples demonstrate the possibilities of monitoring specific damage mechanisms, and specific localizations of wind turbine blades
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