Laboratorio de Pronóstico Inteligente y Sistemas Estructurales Ciber-físicos

This paper presents a mathematical framework for modeling prognostics at a system level, by combining the prognostics principles with the Plausible Petri nets (PPNs) formalism, first developed in M. Chiach´ıo et al. [Proceedings of the Future Technologies Conference, San Francisco, (2016), pp. 165-172]. The main feature of the resulting framework resides in its efficiency to jointly consider the dynamics of discrete events, like maintenance actions, together with multiple sources of uncertain information about the system state like the probability distribution of end-of-life, information from sensors, and information coming from expert knowledge. In addition, the proposed methodology allows us to rigorously model the flow of information through logic operations, thus making it useful for nonlinear control, Bayesian updating, and decision making. A degradation process of an engineering sub-system is analyzed as an…