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Research On Thermography Detection Technology For Impact Damage Of Large Composite Materials

Posted on:2022-11-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:B ZhangFull Text:PDF
GTID:1482306764459084Subject:Instrument Science and Technology
Abstract/Summary:PDF Full Text Request
During the operation of spacecraft in space,it will encounter the impact of space debris,resulting in damage on the surface and sub surface.Therefore,the damage detection and evaluation of protection materials after impact is very important in the process of spacecraft research,on orbit operation and recycling.How to quickly and quantitatively detect and evaluate the damage is one of the difficult problems.Thermography detect has the advantages of high efficiency and simple operation.At the same time,it can detect the damage of sub surface,which can well realize the detection of spacecraft.However,the collected temperature field data contains a lot of redundant information,which affects the characterization of local damage; Limited by the experimental factors such as the detector resolution of thermal imager,it is necessary to mosaic the local damage features of temperature field,but the wrong matching of feature points will cause problems in the visualization of global damage features of temperature field; In the process of high-precision quantitative detection,the thermal diffusion of temperature field and the data aliasing of temperature field lead to the inability to characterize the damage features qualitatively,and can not meet the project requirements.All in all,these were problems that need to be solved in the application of large spacecraft detection.In view of the above application background and related problems,the main researches were as follows.Based on the multi-dimensional representation of the signal,the feature reconstruc-tion model of the temperature field was established.Based on the theoretical analysis of reconstruction model,a temperature field damage extraction algorithm module was pro-posed to accurately obtain the local damage feature image according to the variation law of transient thermal response with time.The temperature field damage extraction algo-rithm module used Pearson correlation coefficient(PCC)to calculate and compare the similarity between the temperature peak with three-dimensional data in the horizontal and vertical directions,and the range size of the window was automatically set according to the threshold for searching the transient thermal response.According to the change trend of transient thermal response obtained by clustering,and the local characteristic image of temperature field damage was obtained.Aiming at the detection of aerospace materials,for solving the problem of mismatch-ing in the process of stitching local damage feature images,the optimal matching algo-rithm of temperature field damage feature was designed to realize the mosaic of tem-perature field damage features of large-scale spacecraft.After extracting the points of the temperature field damage image,in the optimization matching algorithm module,the optimization matching algorithm module was designed.A threshold linear function for finding the accurate affine transformation matrix was designed and feature matching point pairs satisfying the affine transformation function relationship were obtained.The accu-rate feature matching points are used to realize the visualization of local damage features of temperature field.In order to realize the quantitative detection of global damage feature,based on im-age semantic segmentation,hesitation degree and entropy were introduced in the diver-sity optimization fuzzy segmentation algorithm module to design optimization objective function.At the same time,the optimized genetic theory was used to iteratively update the cluster center of temperature field feature data,and the cluster center data meeting the optimization of temperature field feature data was obtained.According to the influence of thermal diffusion effect in the damage,a quantitative detection scheme for the damage feature of temperature field was designed to analyze damage feature.To sum up,aiming at some problems in the process of detection,this dissertation proposed an infrared defect reconstruction model and a temperature field damage extrac-tion algorithm module,which could efficiently and quickly extract the defect.Then the optimization matching algorithm module was designed to mosaic the damage and realize the visualization of damage image.Based on the established diversity optimization fuzzy module,the quantitative detection scheme of temperature field damage was designed to detect the global image of temperature field damage.The feasibility and effectiveness of the model and each algorithm module was verified by experiments.A series of prob-lems caused by the external environment and its own feature in the detection process were solved,and it provided technical assistance for the defect identification and evaluation of large composite materials.
Keywords/Search Tags:thermal imaging technique, image segmentation, feature extraction, damage quantification, image mosaic
PDF Full Text Request
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