Application Of Ultrasonic Testing System Based On LabVIEW In Adhesive Defects

In the process of bonding the thermal insulation component of the outer ceramic matrix composite with the body of the spacecraft,there will be defects due to the poor bonding quality,which is very easy to cause the damage of the thermal protection structure in the flight process,leading to the fall off of the thermal insulation material in the flight process,resulting in unpredictable losses,which is not conducive to the flight safety of the spacecraft.Therefore,it is very important to detect the bonding layer defects of ceramic matrix composite components to improve the flight safety performance of aircraft.Nondestructive testing and evaluation technology is widely used in the bonding defects between such materials and aircraft matrix.In view of this kind of bonding defect,this paper has carried out the research of nondestructive testing technology based on ultrasonic C-scan,including the construction of ultrasonic C-scan testing platform,the principle and imaging method of ultrasonic C-scan testing,and quantitative analysis of bonding defects.First of all,in order to detect the defects of cemented layer of ceramic matrix composite materials,an ultrasonic C-scan detection system based on LabVIEW is built independently.The system integrates two-dimensional mechanical scanning,instrument control and data processing,which can realize the precise control of scanning process and real-time processing of sample scanning data,as well as the original waveform signal diagram,longitudinal section diagram and C-scan diagram The image is displayed on LabVIEW upper computer interface.And save the scanned data for further image processing.Secondly,based on the above saved data,the maximum projection algorithm is used to process the data,and the binary reconstruction image of ultrasonic C-scan detection is obtained,and the adaptive median filter processing is carried out.The C-scan image reflects the cross-section image in the thickness direction.In order to get the defect distribution in the depth of the test sample,the scanning data is reconstructed in two-dimensional slice image at different depth sampling points and superimposed to getthe three-dimensional reconstruction image of the test sample.The three-dimensional reconstruction image can more intuitively see the bonding situation of the internal structure of the whole sample.Finally,the quantitative analysis of adhesive defects is realized by image segmentation technology.For the reconstructed C-scan image,three different algorithms are used for image segmentation and defect smoothing and fitting processing.By comparing three different algorithms,it is concluded that the error of image segmentation using pulse coupled neural network algorithm is the smallest,and the defect detection result is very close to the actual defect of the sample Small,indicating that the system can accurately measure the size of adhesive defects.