A computationally efficient algorithm devoted to gear tooth localized fault detection in induction machine-based systems

This paper presents a fast and computationally efficient algorithm based on the combination of both zoom-MUSIC and zoom-FFT methods for gear tooth localized fault detection in induction machine-based systems. This method relies mainly on the zoom-MUSIC technique for rotor speed estimation at a primary stage and the application of the zoom-FFT to notch filtered instantaneous frequencies of the stator current space vector for the computation of a fault index. It computes the energy of fault-related frequencies in a predefined bandwidth. It will be demonstrated that the fault can be well detected by using only 100 data samples associated with one second data collection of three stator currents. A test-rig based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage helical gearbox has been used for experimental verifications.