Torsional vibration identification using electrical signatures analysis in induction machine-based systems
Midwest Symposium on Circuits and Systems
Fault diagnosis, Gears, Induction motors, Monitoring, Real-time systems, Signal processing, Torsional vibration
This paper deals with a general approach to the feasibility study of the torsional vibration recognition through electrical signatures analysis in induction machine-based systems. The prior works on this specific topic have shown that in case of gear tooth localized fault, the amplitude of main torsional resonance frequency of the electromechanical system was amplified in the stator current space vector instantaneous frequency. Following this initial successful attempt, this work is conducted to establish a common procedure which defines the response of electrical signatures to the torsional vibrations induced by a fault located on the mechanical drive train. The most sensitive electrical signature can be considered for feature extraction and non-invasive torsional vibration analysis accordingly. An experimental setup based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage spur gear is utilized for validation of the proposed approach.
Kia, Shahin Hedayati; Razavi-Far, Roozbeh; and Saif, Mehrdad. (2019). Torsional vibration identification using electrical signatures analysis in induction machine-based systems. Midwest Symposium on Circuits and Systems, 2018-August, 813-816.