Damage Diagnostic Imaging Using Ultrasonic Guided Waves For Key Components In Aerospace Structures

For aerospace structures, efficiency and safety are the eternal pursuit. Structural Health Monitoring (SHM), which integrates intelligent sensor networks and structures to autonomously detect, diagnose and investigate the health state of the structure, is a vital tool to improve the reliability, safety and advancement of aerospace structures. Damage diagnosis is critical to maintaining safe and optimal performance in SHM. Compared with the ultrasonic techniques that use bulk acoustic waves, ultrasonic guided waves such as Lamb waves seem to offer an obvious solution for damage monitoring in large-scale plate-like or pipes components. Therefore it has recently attracted much attention. So far much work have been reported on the damage identification in metal or composite planes and large-diameter pipes, some represented damage diagnostic imaging algorithms have been developed. However, the dispersive and multi-mode nature of guided waves makes the propagation mechanism quite complicated due to geometric and structural complexity in actual aerospace structures, it is quite difficult to interpret the ultrasonic guided wave signals. So for the actual aerospace structures, the experimental studies and applications of them have still lagged behind. Therefore, it is especially important to pay a further attention to the damage diagnostic imaging algorithm in the actual aerospace structures, which is hopeful to promote the aerospace engineering application of SHM technology.This dissertation aims to further develop the key technologies for damage localization and quantification using probability-based diagnostic imaging algorithm with sparse sensor arrangement, and explores new strategies and methods for accurate and efficient damage characterization in complex aerospace structures. To this end, an in-depth research of the following issues has been carried out:analysis and optimization of the influencing parameters in probability-based diagnostic imaging, damage diagnostic imaging in a large-scale curved composite fuselage panel, and guided waves based diagnostic imaging of circumferential cracks in aerospace pipes. The main researches and results are as following:(1) In this article, a methodology to determine the parameters for the PDI algorithm, which are empirically determined in previous studies, has been conducted. Through the analysis of the influence of the parameters affecting the damage identification using the PDI algorithm, the selection of central frequency, the network of sensing paths, and the size of the effective elliptical distribution area are significant from the identification results. Therefore, a fusion image approach of multiple frequencies has been employed to eliminate the influence of frequency selection, while a histogram plot of the differences between the fusion result and the individual results has been introduced for evaluating the reliability and robustness of the fusion images. With the evaluated multiple frequencies fusion imaging, the localization error is obviously reduced and the interference from frequency selection to the other factors is removed. On the other hand, a methodology to optimize network and (3 has been employed for the PDI algorithm, while the points with high unit weight distribution density value have been found to dominantly cause the extremely high probability for the presence of pseudo-damages. Overall, this study is significant for the PDI method to reduce the impact of empirically selected parameters and improve the maturity level of the technology, it could pave a foundation for improving the PDI method.(2) Firstly, this study extended the previous work of probabilistic diagnostic imaging approach and developed a weight compensated-based damage probabilistic diagnostic imaging algorithm to improve the ability of damage localization with higher precision under the same sensor configuration. The process of how to realize the WCPDI algorithm was presented. The effectiveness of the algorithm was thoroughly assessed over several simulated defect locations on a stiffened composite panel. Secondly, the influences of the above-mentioned various factors on the diagnostic image pixel peak value are studied and discussed in detail. Then a novel quantitative guided wave-based damage monitoring method is developed, which is realized with probability by extracting the image pixel peak value, to improve the ability of damage quantification in aerospace structures. The validity of the approach is assessed by quantitative evaluating damages of different extent and at different locations on the stiffened composite panel too. Finally, the challenges and strategies for damage quantification in large-scale aerospace structures are discussed. A fusion localization approach using multiple damage indices is developed to improve the accuracy and reliability of damage localization in large-scale structure. The effectiveness of the proposed algorithms is thoroughly assessed in a full-scale curved composite fuselage panel.(3) The characteristics of guided waves in small-diameter pipes are analyze, it shows that the PDI technique lacks the capability to precisely locate defects in small-diameter pipes since the approximation of the hollow cylinder guided waves by Lamb waves are less suitable in smaller diameter pipe. Therefore, a guided wave-based diagnostic imaging algorithm is developed to improve the ability of circumferential cracks identification in pipe weld. An angular profile-based frequency selection method is presented to ensure the accuracy of the imaging. The effectiveness of the algorithm is thoroughly assessed by a small crack. The circumferential location is determined very accurately. Thus it shows great potential for circumferential cracks identification in pipe weld.