Research Area

  • Title:
    Model-based and Data Driven Fault Detection and Diagnosis

  • Keywords:

    Fault detection, Fault diagnosis, Model-based FDI, Data-driven FDI

  • Description:

    Fault detection and diagnosis (FDD) is one of the key technologies to ensure the safe operation of industrial and autonomous systems. With the widespread application of automation technology and the era of digital systems, model-based and data/signal-driven methods have become a hot research topic in the field of fault detection and diagnosis. In this context, the main research activities regard:
    – Model-based fault detection, isolation and identification in dynamical systems, with applications to mobile robots, robotic manipulators, automation and autonomous systems.
    – Data/signal-driven fault diagnosis, with applications to rotating machines, energy systems, industrial and automation and autonomous systems

  • Laboratory:

    Laboratory of Artificially Intelligent Robotics (LAIR)

  • Contact Person:

    Andrea Monteriù

  • Collaborations:

    University of Lorraine (France)

  • Projects:
    SADABI-IT “Smart Awareness in Digital Automation and Business Intelligence with Integrated Tools” (2019-20224),