“…In this paper, the SHM traditional point of view was applied, using baseline datasets information, and a data-driven method was used for the evaluation and correction of temperature effects [26], assuming that the temperatures distribution field on the sample was homogeneous [27], as well as based on minimizing the difference between several types of baseline tests, adjusting each of them to a reference temperature and, with the use of polynomial regression, being able to estimate the parameters used for compensating a signal recorded at the current damaged state, at a certain temperature at which the baseline data is not available. Finally, to check the effectiveness of the method applied to damage detection and location, the data from the current state were adapted to several available baselines at several different temperatures, and an artificial damage was detected and located, using an imaging algorithm (RAPID, Reconstruction Algorithm for Probabilistic Inspection of Damage) [28] and, based on previous experience [29], a modification of this algorithm (RAPID-G). The effectiveness of the combination of these two methodologies (both signal reconstruction and imaging) is analyzed in this paper, providing a solution to achieve better damage detection and localization in plate-like structures.…”