Research On The Inspection Of Explosive Coated Adhesive Layer Defect Using Infrared Pulsed Thermography And Dynamic Tomogram

Solid engines are widely used in many fields such as rockets and missiles.As an important part of the charging engine,the coating of solid motor grains not only directly affects the ballistic performance of the engine,but also one of the decisive key factors of its service life.Its stability and reliability have been widely concerned.it is easy to produce cracks,pits,bulges,pores or holes,and uneven thickness defects during the process of forming or storing the grain coating,because the grain coating is affected by material characteristics,molding or manufacturing process,storage and transportation,and service environment.The existence of these defects will seriously affect the flammability of the propellant grains,and then affect the service life,working performance,and even safety of the solid rocket or missile engines.In the process of production,storage and service,there is an urgent need for simple,effective and fast non-destructive testing methods or technologies to achieve reliable detection of the coating of solid motor grains.Infrared pulse(thermal wave)imaging and dynamic thermal tomography detection technology is a new non-destructive detection technology with non-contact,intuitive,large detection area,and high efficiency and reliability,which provides a new method for the defect detection of the coating of the grain.Therefore,in this paper,a systematic study of infrared pulsed thermal-wave imaging and dynamic tomography detection techniques for the defects of the coating of the grains is carried out.The pulse thermal response characteristics of the coating layer of the grain under the action of pulse heat flow were investigated.A one-dimensional(1D)analytical model of the pulsed thermal response and a two-dimensional(2D)polar coordinate system heat conduction mathematical model are established.The effects of pulse width,peak energy,defect size and depth on the surface pulse thermal signal are analyzed.The three-dimensional(3D)heat conduction process and temperature field distribution of pulsed heat flux on the coating of grains were studied.Partial least squares regression(PLSR),independent component analysis(ICA)based on principal component analysis(PCA)enhancement,and complex wavelet transform were proposed to extract the pulse heat wave signal feature.The effects and regularities of pulsed thermal-wave signal characteristic distribution or contrast were analyzed by 3D finite element numerical simulation.An infrared pulse(thermal-wave)imaging detection system was developed to achieve efficient and reliable detection of defects in the coating of the grain.Through detection experiments,the feature contrast of different pulse thermal-wave signal feature extraction algorithms and the variation law of the defect signal-to-noise ratio(SNR)were studied.The defect detection ability of various feature extraction algorithms(Fast Fourier transform FFT,PCA,PLSR and ICA)is analyzed,and the correctness of simulation results is verified.The blind separation edge enhancement method of the infrared pulse thermal-wave characteristic image for the defect of the coating layer is studied,and the main noise sources and characteristics of the characteristic image are analyzed.The enhancement effect of the classic image enhancement algorithm and wavelet transform enhancement algorithm on the pulse thermal wave characteristic image is investigared.The influences of wavelet basis functions,wavelet decomposition layers and threshold algorithms on wavelet transform blind separation to enhance noise reduction ability are discussed.The defect edge extraction method and defect size detection method are researched.For larger-size grains of coating defects(diameter ?8mm),the deviation of the defect size detection is less than 5%.Dynamic thermal tomography(DTT)detection technique of infrared pulsed thermal-wave imaging for the coating defects was studied.A DTT method based on the fusion of pulsed thermal wave feature maps was proposed to realize the interior of the grain coating samples 3D visual inspection of defect distribution and morphology.The maximum relative deviation of defect depth in tomographic inspection is <20%.A DTT method based on complex wavelet transform CWT is also discussed.This method can also realize tomographic detection of defects in the coating layer of the grain,but the deviation of the depth of the tomographic detection is relatively large.