Current Measurements for Fault Diagnosis in Induction Motors

Predictive maintenance has become increasingly important in modern industry as it can prevent unplanned production interruptions and reduce maintenance costs. This is especially important for companies working with expensive and complex machinery, such as those used in manufacturing, transportation, and energy. Predictive maintenance uses sensors and data analytics to monitor equipment performance and predict when a failure or breakdown might occur. This paper presents a preliminary study on the use of absorbed currents measurement of a three-phase induction motor aimed at electrical fault diagnostics. In detail, a 4-pole high efficiency induction motor with 3kW of rated power was simulated in the Ansys Electronic Desktop environment. The simulated operation is with direct mains power supply. The motor was simulated initially at no load, then load torque values of 20%, 40%, 60%, 80% and 100% of rated value were evaluated. The currents drawn on the three phases were evaluated with a computational step of 500 us, corresponding to a sampling rate of 2 kHz. The same simulations were subsequently repeated by reproducing five different fault conditions in the motor. Therefore, an analysis of the waveforms of the absorbed currents is provided and a diagnostic system based on their analysis is proposed.