Combining experimental and computed data for effective SHM of critical structural components

A highly effective Structural Health Monitoring, SHM, system for aerospace applications must be, besides highly reliable, a low complexity and low weight solution.^1,2 This can be achieved with a reduced number of sensors, which normally implies a low resolution mapping of the monitored variables and, consequently, a weakness on the diagnosis and prognosis procedures. To overcome these difficulties, the physical information from the sensing network can be complemented with a virtualization of the representative geometry and physics of the structural system. This article proposes an integrated procedure to analyze structural health of critical system, combining experimental data from a sensor network with a computational model of the structural system. This approach involves vibration-based monitoring and diagnostic. The SHM technology is applied to a reinforced carbon fiber plate having different damage levels. This flat plate with z-shaped stiffeners is instrumented with accelerometers. The location of sensors is optimized for maximum detection capability using computer simulations (Abaqus®) and a custom developed algorithm. Computational simulations of the vibration behavior of the monitored structural component are also performed to validate the damage diagnosis concept and analyze the sensitivity of the method in damage detection. Furthermore, the data from sensors are compared with the simulation results. The method is able to detect, locate and assess the damage severity, becoming a power tool for damage diagnosis of structural components. Finally, a SHM platform that allows the combination of physical and virtual data for damage diagnostic, PRODDIA®, is presented.