Abstract

Damage modes of composite wind turbine blades mainly include the damage and delamination of skin and web as well as the adhesive failure between the web and skin. This chapter performs acoustic emission (AE) tests, defects positioning, and damage mode identification of full-size glass fiber/epoxy composite wind turbine blades under bending fatigue loading. Eight sensors are grouped into two parallels and each parallel is set inside the local rectangular area at the adhesive of skin/web, near 1/3 of blade root of blade. Then, the AE signal parameters such as amplitude and duration are extracted and dimensioned and clustered. Due to the low accuracy of the method of identifying damage modes only by clustering results analysis, a method of optimizing data sets by matching the clustering results of AE source signals with the information of two-sensor plane locating points are further developed, and a damage pattern recognition model is established. This work promotes the application of AE technology in wind turbine blades, providing powerful theoretical and technical support for on-line monitoring, AE source localization and dominating damage mode identification of wind turbine blades.

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