Digital Correction of the Health Status of an H/F Electrical Network

Job description: Cable defects are usually detected when communication is interrupted, resulting in significant repair costs and time. In addition, data integrity is becoming a major issue due to the increased threats of attacks and intrusions on electrical networks that can disrupt communication. Being able to distinguish a disturbance due to the degradation of the physical layer of an electrical network or to an ongoing attack on the energy network will guide decision-making regarding correction operations, including network reconfiguration and predictive maintenance to ensure network resilience. In this post-doc, you will study the relationship between emerging cable defects and their impact on data integrity in power line communication (PLC). Your work will be based on the deployment of instrumentation using electrical reflectometry, combining distributed sensors and AI algorithms for online diagnosis of emerging faults in electrical networks. In the presence of certain defects, advanced AI methods will be applied to digitally correct the health of the physical layer of the power grid and thus ensure its reliability.

Your profile: Doctorat en systèmes de communication ou traitement du signal