Diagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithm - Cavalcanti, Rafael (2025)
This study developed an algorithm running on the cloud that makes data process and diagnoses broken rotor bar faults in three-phase induction motors (TIMs), by analyzing stator dynamic deformation using fibre Bragg gratings (FBGs) as sensors. This method can diagnose mechanical faults (misalignment, imbalance) and electrical faults (fractures or cracks in rotor rings or bars). FBG-based sensors were used due to their high multiplexing capability, electromagnetic radiation immunity, and long-distance operation. Tests were conducted on a small-scale induction motor (3 HP) coupled to a generator to simulate load and the generator supplied by the grid. Were used 1 healthy rotor and one rotor with a broken bar fault running at two load conditions, 75% and 100%. The algorithm successfully identified broken bar faults in two frequency regions: around the mechanical rotational frequency of the rotor 28.06 Hz and 31.014 Hz operating at 75%; 25.325 Hz and 32.995 Hz operating at 100% and approximately twice the electrical frequency supply, 118.455 Hz and 123.942 Hz operating at 75%; 117.237 Hz and 124.683 Hz operating at 100%. The system showed high sensitivity, a good signal-to-noise ratio, and advantages over conventional methods for detecting broken bar faults in induction motors.