The aim of the project is to achieve reliable non-destructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. For instance, ultrasonic NDE methods are sensitive to elastic properties and density and are good at detecting planar defects such as lack of bonding/delamination; however, they may suffer from attenuation or diffraction. X-rays are very sensitive to changes in density and volumetric defects, but their performance on planar defects is limited. Combining the information obtained by different methods has the potential to improve the reliability of NDE.
The object of the planned research is adhesively bonded aerospace components, whose usage in aerospace industry is still limited due to lack of reliable NDE methods – many bond failures were traced back to insufficient quality control. The quality evaluation of joints using non-destructive testing (NDT) methods is required for different industries including aerospace. Currently, adhesive joints are allowed only in secondary load carriers because there is no single NDT technique that would reliably detect adhesive defects and weak bonds. The reliable NDE of adhesive joints is expected to be achieved by using multidimensional data fusion of ultrasonic and X-ray NDT techniques.
During the implementation of this project: multidimensional data fusion techniques will be developed for the fusion of data obtained using ultrasonic and X-ray NDE techniques to detect adhesive defects in complex composite structures and to evaluate the quality of the joint. Improved detectability of different types of defects achieved by multidimensional data fusion techniques in comparison to existing single NDT techniques will be achieved. For the reliability evaluation of the results obtained by each NDE technique and data fusion, the probability of detection (POD) will be estimated. The results obtained during the implementation of the project will be disseminated in international conferences and scientific articles published in foreign scientific journals with an impact factor.
Project funding:
Projects funded by the Research Council of Lithuania (RCL), Projects carried out by researchers’ teams
Project results:
Feature-based data fusion technique to improve the probability of defect detection in the adhesive lap joints was developed. Data were experimentally obtained using two common NDE techniques: ultrasonic pulse-echo and radiography. For this investigation, single lap adhesive-bonded aluminum joint with different sizes of brass inclusions were used. For the analysis, several distinctive features were extracted from the experimental ultrasonic and radiographic data and used as inputs for data fusion. The comparison of extracted features shows that, at least in the case of the inclusion type of defect, the most promising features giving the highest contrast in terms of the defect/non-defect region from ultrasonic images are signal attenuation, peak-to-peak amplitude, and absolute energy; however, other features, especially frequency domain related, should not be disregarded. The fused image provides intricate details of the defects in the sample on a finer scale. Although radiographic image contributes to the detection of the inclusion type of defect the most, the ultrasonic image provides extra information about additional types of defects, such as disbonds around the edges of the inclusions, which are not visible in the radiographic images. Of the fusion algorithms used, the best performance was achieved using average and saliency algorithms—AUC values of more than 0.99 are achieved.
Project documents:
Non-Destructive Evaluation of the Quality of Adhesive Joints Using Ultrasound, X-ray, and Feature-Based Data Fusion | APP122412930 |
Period of project implementation: 2022-04-01 - 2025-03-31
Project coordinator: Kaunas University of Technology
