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This paper presents the development and validation of a low-cost device for real-time detection of fatigue damage of structures subjected to vibrations. The device consists of an hardware and signal processing algorithm to detect and monitor variations in the structural response due to damage accumulation. The effectiveness of the device is demonstrated through experimental validation on a simple Y-shaped specimen subjected to fatigue loading. The results show that the device can accurately detect structural damage and provide real-time feedback on the health status of the structure. The low-cost and easy-to-implement nature of the device makes it promising for use in structural health monitoring applications in various industrial sectors. [ABSTRACT FROM AUTHOR]

Additive manufactured structures are replacing the corresponding ones realized with classical manufacturing technique. As for metallic structures, 3D printed components are generally subjected to dynamic loading conditions which can lead to fatigue failure. In this context, it is useful, and sometimes mandatory, to determine the fatigue life of such components through numerical simulation. The methods currently available in literature for the estimation of fatigue life were originally developed for metallic structures and, therefore, it is now necessary to verify their applicability also for components fabricated with different materials. To this end, in the current activity three of the most used spectral methods for the estimation of fatigue life were used to determine the fatigue life of a 3D printed Y-shaped specimen realized in polylactic acid subjected to random loads with the aim of determining their adaptability also for this kind of materials. To certify the accuracy of the numerical prediction, a set of experimental tests were conducted in order to obtain the real fatigue life of the component and to compare the experimental results with those numerically obtained. The obtained outcomes showed there is an excellent match between the numerical and the experimental data, thus certifying the possibility of using the investigated spectral methods to predict the fatigue life of additive manufactured components. [ABSTRACT FROM AUTHOR]