Research On The Detection Experiment Of Defects In CFRP/Al Honeycomb Structure By Pulse Infrared Thermal Wave And The Algorithm Of Thermal Wave Signal Processing

Honeycomb sandwich structure has good impact resistance,light material,high temperature resistance,corrosion resistance and other properties,It is widely used in aerospace,supersonic aircraft,ship industry and other fields.During the service of Honeycomb sandwich structure,the bond between the honeycomb core and skin is easy to solidify,resulting in debonding defect.Therefore,it is necessary to detect debonding defects of honeycomb sandwich structure.Infrared thermal wave nondestructive testing technology has the advantages of fast detection speed,high detection accuracy and large detection area,which provides a new method for the defect detection of honeycomb sandwich structure.This paper based on the theory of infrared heat wave detection,the transient heat conduction analysis of honeycomb structure under pulse excitation is completed;based on the analysis of infrared heat wave detection principle,the construction of pulse infrared heat wave detection system is realized,and the design of heat excitation system,thermal imaging system and image processing and analysis system is completed.The specimen of CFRP / Al honeycomb plate simulating the debonding defects were made.Based on the established test system,the test of detecting the debonding defects of the honeycomb plate by pulse infrared thermal wave was carried out.The effects of defect diameter,defect depth,heat flow power and pulse width on the test results are analyzed.The pulse phase Thermography(PPT)method,principal component analysis(PCA)method,thermal wave signal reconstruction(TSR)method,total harmonic distortion(THD)method and other infrared thermal wave signal processing algorithms are studied,and the effects of the above algorithms on the infrared image processing of CFRP / Al honeycomb plate are compared and analyzed.Through histogram enhancement,contrast enhancement and filtering,the infrared image processed by THD method is enhanced,and through iterative threshold segmentation,Otsu threshold segmentation and region growing method,the infrared image segmentation is realized.Based on classical edge detection operator,particle swarm optimization imagesegmentation algorithm and morphological algorithm,The infrared image defect edge detection of honeycomb structure is realized,The edge detection results of different algorithms are compared and analyzed.The results show that the edge recognition effect of morphological algorithm is better than that of classical edge detection operator and other algorithms,which can realize the edge recognition of honeycomb structure defects.