Defect Depth Retrieval Method Based On Nonlinear Trsformation For Pulsed Thermographic Inspection

Carbon Fiber Reinforced Polymer(CFRP)is an emerging material with excellent properties such as high toughness,high strength,corrosion resistance,and high temperature resistance.It has been widely used in aerospace,fitness equipment and other fields.Due to the complex manufacturing process of composite materials and the susceptibility to external forces such as friction or impact during use,the materials will have varying degrees of defects.Optical infrared thermal imager(Optical Infrared Thermography,OT)non-destructive testing technology has the characteristics of large detection area,convenient operation,simple,etc.,and is widely used in composite material defect detection to ensure the engineering quality of specimens.Defect detection is generally divided into two directions: qualitative and quantitative.Qualitative detection aims to find the location of defects,study data processing algorithms,enhance the signalto-noise ratio of the image and the detection rate of defects;quantitative detection includes detecting and quantifying the size and depth of defects.In this paper,a nonlinear transformation model based on the peak time of temperature contrast is proposed,and the defect depth is predicted by light-excited thermal imaging technology.The experiment verified the mechanism of the non-linear relationship between peak contrast time and defect depth.In order to effectively predict the depth of defects,Gaussian transformation is used for nonlinear transformation in depth detection.Experimental results show that this proposed method improves the accuracy of defect depth measurement.The main research contents and innovations of this paper are as follows:1)This paper introduces the current research status of non-destructive testing technology at home and abroad,expounded the commonly used defect depth detection methods,made a detailed analysis of the basic principles of light-excited thermal imaging technology,introduced light-excited infrared system equipment,and introduced common data processing methods and signals The incentive model was discussed and analyzed.2)Two physical models of heat conduction under different excitations are compared: 1)the traditional light-excited thermal imaging technology of the flash lamp heat source;2)the light-excited thermal imaging technology of the halogen lamp heat source.The temperature response of the specimen surface under the two excitation modes was compared,and the depth prediction method and adaptability under the excitation mode of flash lamp and halogen lamp were compared.3)An innovative method for predicting the depth of defects is proposed.On the basis of the short-pulse excitation model,the physical model of heat conduction of long-pulse thermal imaging was expanded,and a nonlinear heat conduction model between characteristic time and defect depth was established,and the nonlinear model was transformed into a linear model by Gaussian transformation.The linear model is used to predict the depth of the defect,and a large number of experiments are used to verify its accuracy.