Research On Defect Detection Technology Based On Active Microwave Thermal Imaging

Absorbing coating materials have a wide range of applications in achieving stealth or shielding interference.It absorbs and attenuates electromagnetic waves by dissipating incident electromagnetic waves in the form of thermal energy or attenuating them in the form of resonance.The defects of the wave absorbing coating have a significant impact on the wave absorbing performance,and it is usually necessary to strictly control the defects of the coating to ensure the stability of the wave absorbing performance.Therefore,the defect detection technology of the absorbing coating material is particularly critical to the guarantee of the stealth performance of the target and the shielding performance of the electronic system.The active microwave thermal imaging method has the advantages of high heating efficiency and uniform heating in the defect detection of absorbing coating materials.Therefore,this thesis studies the defect detection of absorbing coating materials based on the active microwave thermal imaging method.Aiming at the difficulties of defect depth detection and insufficient defect size detection accuracy in the current absorbing coating materials,combined with the characteristics of the heating and cooling process of the absorbing coating,this thesis proposes a method for defect depth detection during coating heating process and defect size detection during coating cooling process.In order to realize the detection of the depth and size of defects in the absorbing coating during the heating and cooling process,a hardware system is designed,which mainly includes: aiming at the uniformity and high efficiency of the heating of the coating sample,a heating antenna is designed;For the control of the heating and cooling process,the motor control system is designed;For the hardware composition,the power amplifier,frequency source and infrared imager are selected,and the detection environment is built and the test software is written.In the defect size detection method in the cooling process,the original infrared cloud image detected by the coating sample is taken as the object,and the original detection cloud image is preprocessed;The limitation of edge discontinuity of classical edge detection operator and the problem of threshold misjudgment in traditional morphological edge detection are analyzed.To solve this problem,an improved morphological edge detection algorithm with double threshold segmentation is proposed,and the detection results are quantitatively compared.The results show that: compared with the traditional algorithm,the algorithm proposed in this thesis reduces the defect area size error by more than 15%,and the defect location error rate reduces by more than 20%.In the defect depth detection method in the cooling process,a defect depth detection based on active microwave thermal imaging is proposed to solve the problems of large detection error and excessive dependence on sample data in the current infrared nondestructive defect depth detection based on the surface temperature and depth fitting of the sample.The specific relationship between defect depth and surface temperature is established,and the numerical verification of the algorithm is carried out.The results show that the error of the algorithm deduced in this thesis is within 2%.