Combinando o Filtro de Kalman com um modelo de dano contínuo para a identificação de dano e avaliação de vida residual

Abstract

This work was inspired in Digital Twin concept to monitor, in real time, the integrity of physical dynamic systems throughout its operating cycle. Its methodology consists of creating a digital copy to monitor the health of a structure, based on physics and data, in addition to building an approach to identifying and predicting damage based on phenomenological models [1]. Digital Twin would be connected to your physical system through the sensors installed on site, allowing you to monitor it throughout its life cycle. Then, the optimization of the physical system and decision-making would depend on the responses generated by Digital Twin. In this dissertation, the results of the computational method built from phenomenological models and Kalman filter using the Digital Twin concept will be presented, whose purpose is to support prognoses of structural failures over time.