Research On Defect Monitoring Of Composite Wind Turbine Blade Based On Acoustic Emission Technology

As a clean and renewable energy source,wind energy is receiving more and more attention from all over the world.Wind turbine blades are an important part of wind power generation systems.Carbon fiber(or glass fiber)reinforced epoxy resin composite materials have been widely used in wind power blades due to their advantages of high specific strength,specific stiffness and good fatigue resistance.However,the damage failure mechanism of composite blades is very complex,usually including fiber fracture,matrix cracking,interface debonding and delamination,among which delamination and interface bonding will seriously reduce the stiffness,strength and structural integrity of composite materials.The service environment of wind turbine blades is mainly the fatigue load condition.From a design perspective,the research on the fatigue performance of wind turbine blades is very critical.The operating environment and load of wind turbine blades are very complex,which poses a challenge to accurately predict the damage tolerance and fatigue life of the structure.A large number of studies on damage and failure mechanism of composite materials based on acoustic emission technology have been carried out at home and abroad.However,most of the studies are limited to material level.However,there is little work on acoustic emission defect monitoring and damage mode identification of full-scale wind turbine blade structures,so it is urgent to carry out relevant application research.To this end,this paper firstly studies delamination behaviors of carbon fiber/epoxy composite laminates under different loading rates using acoustic emission(AE)that shows a large advantage for dynamic monitoring of instantaneous defects by analyzing characteristic signal parameters.After that,the acoustic emission test of composite specimens under tension-tension fatigue load is carried out.After noise reduction of acoustic emission signal,the line location of the real-time defects of the composite specimens is completed,and the reliability and superiority of pattern recognition by peak frequency are verified.Finally,the acoustic emission test of full-size wind turbine blades with glass fiber/epoxy composites under fatigue loading is carried out.After noise reduction of acoustic emission signal,the rectangular plane location of the real-time defects of the composite specimens was completed.Then the acoustic emission 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 in blades only by clustering results analysis,this paper develops a method of optimizing data sets by matching the clustering results of AE source signals with the information of two-sensor plane locating points,and then establishes a damage pattern recognition model.This work promotes the application of acoustic emission technology in composite materials and full-size wind turbine blades,providing powerful theoretical and technical support for on-line monitoring,acoustic emission source localization and damage pattern recognition of full-scale wind turbine blades.