Application Of Pulsed Infrared Thermal Wave Technology In Dedect Detection Of Composite Materials

Pulse infrared thermal wave detection technology is a new type of active non-destructive detection technology.Compared with other non-destructive detection technologies such as ultrasound,eddy current,and radiation,it has the advantages of low cost,large detection area,wide application scenarios,and low harm to humans.In recent years,this technology has been widely used in the field of non-destructive testing of composite materials.In this paper,a typical non-metal-metal laminate composite is taken as the research object,and its pulse infrared thermal wave detection process is numerically simulated and experimentally analyzed.By processing the acquired infrared image sequence,the defect feature extraction is completed.In terms of numerical simulation analysis,COMSOL software was used to conduct a finite element simulation analysis of the infrared thermal wave detection process.Complete the creation of the carbon fiber-aluminum alloy laminate with a debonding defect model and the solution of the model.Research and analysis of temperature distribution changes on the surface of the test piece model,the feasibility of the pulse infrared thermal wave detection technology for the defect detection in carbon fiber-aluminum alloy laminates was verified.By comparing and analyzing the difference in the temperature change trend between the defective and non-defective areas,it is concluded that the larger the size of the defective area,the easier it is to be detected.In terms of the pulse infrared heat wave detection experiment,the carbon fiber-aluminum alloy laminate with debonding defects is tested experimentally.Analyze the performance characteristics of the flash pulse excitation infrared detection platform,and design experimental schemes and steps.By adjusting the pulse excitation energy,the excitation pulse width,and the detection distance,the optimal parameter setting combination is obtained,and the infrared image imaging quality and defect detectionaccuracy are improved.And extract the compressed data collected in the experiment,the infrared image sequence is constructed to prepare data for subsequent image sequence processing research.In terms of infrared image sequence processing,this paper proposes an image sequence processing algorithm based on Retinex-PCA,which is compared with the processing results of singular value decomposition algorithm and principal component analysis algorithm.The comparison results show that: Compared with the singular value decomposition algorithm,the Retinex-PCA algorithm reduces the loss of defect details in the image;Compared with the principal component analysis algorithm,on the basis of compressing and reducing the size of the infrared image sequence,the problem of lower defect contrast is improved,and the performance of defect feature extraction is better.