Self-sustainable IoT Wireless Sensor Node for Predictive Maintenance on Electric Motors
Unexpected equipment failure is expensive and potentially hazardous for workers and users.
Periodic inspections and maintenance at predefined intervals aim to limit unplanned production downtime, costly replacement of parts and safety concerns. On the other side, predictive maintenance techniques can monitor equipment as it operates, anticipating deterioration and incoming breakages, enabling just-in-time services at reduced operational costs.
This project relates to the research and development of a deploy and forget predictive maintenance sensor node designed explicitly for industrial electric motors. The sensor will measure vibrations, environmental noise, temperature, and the external magnetic field.
The sensor will be required to achieves self-sustainability by exploiting a thermal source and it will feature short-long wireless data transfer respectively over WiFi and the cellular NB-IoT network.
