Fabrício Alves de Almeida

TL;DR: A method of multiobjective sensor locations optimization using the collected information by Fisher Information Matrix (FIM) and mode shape interpolation is presented and shows that the proposed method is effective to distribute a reduced number of sensors on a structure and at the same time guarantee the quality of information obtained.

TL;DR: In this article, an optimized methodology for delamination identification on laminated composite plates involving the use of reduced mode shapes and computational tools, i.e., Genetic Algorithm (GA) and Artificial Neural Networks (ANN) is performed.

TL;DR: The neural network created based on this study’s methodology presents extremely reliable results, allowing a quick and robust diagnosis of the motor operating condition.

TL;DR: The obtained results indicate that the proposed Structural Health Monitoring method can successfully identify the location and the severity of small induced damage cases in the laminated composite plate and the improved algorithm was shown to be more efficient and accurate than the widely known and applied Genetic Algorithm.

TL;DR: In this article, the use of an inverse method for delamination identification in carbon fiber reinforced polymers plates was proposed, where the inverse problem was solved by minimizing an objective function through genetic algorithms.