Advanced and Smart Maintenance of Induction Motors Based on an Algorithm for Motor Faults Recognition

The paper describes the algorithm and the methodology to recognize rotor faults of the squirrel-cage motor based on the induced voltages in the measuring coils spatially spaced for the pole pitch. Based on the FEM calculations and measurements, the functional algorithm for early fault detection and reliable recognition of rotor faults was designed. In the paper is presented and described flowchart of the proposed algorithm. Furthermore, the two special algorithms were designed, based on the obtained research results. The input parameters for the proposed algorithm are induced voltages in four measuring coils spatially spaced for pole pitch. The first algorithm is intended for early and reliable detection of the broken rotor bars and the broken ring of the squirrel-cage induction motor. The second algorithm is proposed for early and reliable detection of the rotor static eccentricity. The proposed algorithm uses induced voltage in four measuring coils. In the case of the broken rotor bars and ring, the algorithm uses voltage difference between two induced voltages in measuring coils spatially spaced for $2 \tau_{\mathrm{p}}$. In the case of static eccentricity, the difference between the RMS value of each measuring coil installed in the air gap of the induction motor is analyzed. The proposed algorithms are aimed to improve and contribute to the advanced and smart maintenance of induction motors.