(untitled) (Research, Society and Development, 2022)
In this paper presents an artificial intelligence system based on artificial immune systems for analyzing the structure of a metal bridge. Inspired by a biological process, the negative selection algorithm is used to carry out the identification and characterization of structural failures. This tool will help identify the maintenance, configurations of structures, the way to identify failures, in order to ensure the health quality of the structure and carry out security decisions. To validate the methodology, were used a real data obtained from laboratory experiment, and from this, several situations were generated (normal and fault conditions), obtaining a database of signals, which were analyzed by the method proposed. The results obtained by the negative selection algorithm are efficient and robustness. It is worth mentioning that artificial intelligence with signal processing allows for a higher quality in the diagnosis. Thus, this article contributes to the lines of research in structural health monitoring and artificial intelligence, presenting a very efficient methodology.