Research On CFRP Damage Detection And Evaluation Based On Eddy Current Image Processing

Carbon fiber composite is a perfect combination of carbon fiber and plastic.Compared with metal,it has its advantages: strong,hard,especially light weight.In many fields such as industrial production,aerospace and public infrastructure,the selection of structural materials plays an important role in the innovation of technical level and the improvement of product quality.Among all kinds of new composite materials,carbon fiber composite has been used in many occasions because of its superior structural characteristics.However,there are many uncertain factors in the multi-phase structure of CFRP and its manufacturing method,which make the internal defects in raw materials and semi-finished products and the structural damage in the processing and use of molded parts inevitable.In this thesis,the results of eddy current testing are presented as images,which contain a lot of structure and damage information of the tested parts.Therefore,it is necessary to process the images to obtain these information.Combined with the image processing of neural network genetic algorithm,the micro structure damage and damage location of carbon fiber composite plate can be determined.The main contents of this paper are as follows:First,in order to establish the modeling and simulation of eddy current imaging system,the influence of crack depth on the scanning results and the influence of defects in the scanning fiber lines are studied.Firstly,the eddy current imaging system is modeled and analyzed,and then the transfer function of the imaging system is obtained from the point spread function.Finally,the electromagnetic finite element simulation model of CFRP and the fiber pattern imaging simulation model of ECT are established.In order to achieve high precision imaging of fiber orientation and ply defects in CFRP laminates,the images can reflect the true shape of composite defects.Secondly,in order to better evaluate the damage parameters of CFRP and locate the defects in the images of the laminates in each specific direction.Firstly,the pseudo color image of multi-directional laminate is generated by eddy current C-scan,and the generated pseudo color image is processed in the complex plane to obtain a clear and intuitive pseudo color image.Then,based on MATLAB and combined with the digital image processing methods in time and frequency domain,including fast two-dimensional Fourier transform and inverse transform,notch filter design and construction,the different directions of the texture of carbon fiber composite plate image are separated,so that the texture direction and defect position in the composite material laminate eddy current C-scan image can be seen more clearly and intuitively.Finally,by using the deconvolution image de aliasing method,the processed image can more clearly identify the fiber deformation,fiber direction,dislocation and micro damage in the layer.Thirdly,the eddy current testing of composite materials is mainly based on the analysis of the eddy current testing signals to determine whether there are cracks and layered damage structures in the composite materials.In order to quantitatively analyze the defect damage,neural network algorithm is needed.Firstly,the structure and location of various damaged structures are analyzed by simulation and experiment,and then a set of neural network genetic algorithm is compiled to identify and locate the damaged structures.Finally,the quantitative analysis of defects in CFRP materials is well based on neural network algorithm.