Detection, Location and Quantification of Structural Faults in a Two-Story Building Using the Artificial Immunological System

Large buildings and skyscrapers are vulnerable to environmental, temporal, and anthropological stresses, generating wear and tear that can lead to this social and economic impediment's collapse. The technological improvements of the fourth industrial revolution have resulted in changes in the connection between physical space and man, known as the cyber physic model, which necessitates monitoring systems to protect the structural branch and so correct this structural vulnerability. Thus, the structural health monitoring system is the exact measure of the evolution required by the cyber physic model in construction and the protection of the monumental buildings, ensuring not only their economic development but also the safety of society. Therefore, this research work presents the innovative proposal of the cyber-physical structural health monitoring system aimed at buildings and skyscrapers, based on and differentiated by intelligent computing techniques, using the negative selection algorithm to perform the analysis and monitoring of structural integrity, overcoming the existing traditional work. The cyber-physical structural health monitoring system will be applied to experimental data obtained from the shear building model that represents these imposing skyscrapers. An artificial immune system will be developed and used in the decision-making process based on the acquisition and processing of the obtained signals to perform the identification, localization, and quantification of possible structural damage. Observing the results, this work proved to be efficient, robust, and economically feasible, having high performance and overcoming the shortcomings of traditional techniques. It represents the perfect measure of cyber physics in the monitoring of large buildings and skyscrapers.