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Structural Integrity through Vibroacoustic Modulation (VAM) for Lifecycle Extension of Civil Infrastructure    

Methods of Artificial Intelligence, networked embedded systems, non-destructive testing, and innovative sensing are applied jointly to develop a method for microstructural damage detection using Vibroacoustic Modulation (VAM) long before a macrostructural crack occurs in the structure; hence, ensuring sufficient time for taking suitable measures. Existing approaches use concepts that, at present, do not allow life cycle prediction and do not provide sufficient local resolution. In contrast, the VAM method permits an entirely new system design, including data pre-evaluation on the sensor nodes to ensure high resolution even at large structures. Objectives of the project are, among others, new knowledge in fundamental science, sustainable use of resources, reduction of maintenance cost, and increase of civil safety to the advantage of economy and society, through tailored maintenance of infrastructure. Hence, time and expenses are minimised by an efficient, wireless, cost-efficient, and regeneratively powered sensor network. Fourier-transformed VAM spectra are perfectly suited for evaluation with Artificial Intelligence (AI) and will be evaluated continuously. We expect this to lead to a reliable assessment of the structural health condition similar to the long-term cardiogram applied for humans. Additionally, the analysis of VAM provides new insights into crack initiation and progression and the degradation of metal and composite materials subjected to cyclic fatigue loading, thus enabling the determination of defect type and defect location.