Three-Phase Induction Motor Monitoring System for Predictive Failure Analysis Based on Digital Twin, IIoT and Finite Element Method

As technology in industry advances and competition for maintenance efficiency intensifies, the industry is looking for more resources to ensure the reliability of its processes.Thus, this paper proposes a tool to optimize the Monitoring and Analysis System (from Portuguese, Sistema de Monitorização e Análise de Motores - SMAM), a tool that helps predictive maintenance of three-phase electric motors through the use of Digital Twin (DT). Therefore, the current of the three motor phases are monitored, as well as temperature and voltage. These measurements are collected by the ESP32 microcontroller and sent to the Firebase database. This current data is fed into the motor simulation performed in Finite Element Method Magnetics (FEMM) software. This simulation run on a virtual machine and the simulation results are stored in the database and can be viewed on a dashboard that shows the progress of each simulation. In this way, the user can check the magnetic flux and the internal temperature of the motor in real time for more precise monitoring of its operation.