Supported by the framework of iNEST (https://mathlab.sissa.it/project/interconnected-nord-est-innovation-ecosystem-inest) and organised together with Wärtsilä, the Smart Vibration Assessment Service (SVAS) project aims to develop cutting-edge solutions for predictive maintenance. The study focuses on the diagnostics and health assessment of bearings, as they are mechanical components widely used in industrial equipment.
Vibration analysis is leveraged to monitor the condition of bearings and get information regarding the mechanical behaviour of the system. The identification of patterns associated with incipient faults would allow to foresee failures in advance. This is particularly relevant in industrial settings, where early fault detection enables more efficient maintenance planning, minimizes unexpected downtime, and helps ensure continuous, cost-effective operation.

mathLab members involved: Elvin Babayev, Giuseppe Alessio D'Inverno, Gaia Marsich, Fatemeh Mohammadizadeh, Ivan Prusak, Gianluigi Rozza