This research focuses on the development of a damage detection algorithm based on modal testing, vibrothermography, and feature extraction. The theoretical development of mathematical models is presented to illustrate the principles supporting the associated algorithms, through which the importance of the three components contributing to this approach is demonstrated. Experimental tests and analytical simulations have been performed in laboratory conditions to show that the proposed damage detection algorithm is able to detect, locate, and extract the features generated due to the presence of sub-surface damage in aerospace grade composite materials captured by an infrared camera. Through tests and analyses, the reliability and repeatability of this damage detection algorithm are verified. In the concluding observations of this article, suggestions are proposed for this algorithm’s practical applications in an operational environment.

This article presents a novel modal-based vibrothermographic approach for health monitoring of loosening bolted joints in coupled structures. In this article, the theoretical background supporting this proposed approach is firstly presented. Through finite element analyses on a simple bolted structure with varying joint conditions achieved by adjustment of bolt loads, the relationship between the bolt load and the temperature increase in the vibrating bolted joint during vibrothermographic tests was revealed. Experimental vibrothermographic tests on a more complex structure were completed to verify the observations from the finite element analyses while demonstrating the viability of the vibrothermographic approach in a laboratory environment. It has been shown that this vibrothermographic approach was able to determine the stage of a bolted joint in its progression of failure by tracing the changes in the temperature increase in relevant regions during vibrothermographic tests. Moreover, additional tests have been performed to illustrate that this approach was effective even by using only the residual responses of the structure's vibration that were away from the resonances, which indicates it is more applicable to structures with higher damping as such structures have stronger residual responses during vibration that can be utilized. In the concluding observations of the article, the procedure for practical application of this approach is summarized, and its potential for further development is discussed.

This research focuses on the verification of the viability of image compression in infrared thermography in order to address the problem of data storage. Specifically, images from vibrothermographic tests were utilized due to their special characteristics compared to the results from alternative infrared thermography techniques, which are able to introduce additional uncertainties to the compression process. In this research, an adaptive algorithm based on the lifting discrete wavelet transform and setpartitioning embedded blocks was used for image compression. Five different methods, namely the compression ratio, mean squared error, peak signal-to-noise ratio, structural similarity index and coordinate modal assurance criterion, were applied to evaluate the performance of the compression process while identifying and locating the regions affected more significantly after image compression. Feature extraction through the independent component analysis was then applied to the images to separate the features such as the hot spots so that the influence from the image compression process on each important feature could be evaluated independently. In this article, the theoretical background of the applied data processing techniques is firstly presented. Through two sets of data acquired from vibrothermographic tests on an aerospace-grade composite plate containing delamination, the effects of the image compression process on the relevant hot spots are evaluated, and the effectiveness of the compression process is verified. It is demonstrated that the compression process was able to reduce the size of the images significantly without adversely affecting the quality of the important features indicating the presence of damage. The major characteristics of the key features have been successfully preserved after effective image compression.

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