Stator Current Analysis From Electrical Machines Using Resonance Residual Technique to Detect Faults in Planetary Gearboxes

Motor current signal analysis (MCSA) provides an alternative nonintrusive approach to detect mechanical faults by using the fault signature transmitted along the torsional direction through the rotor. In existing fault detection methods based on MCSA, the gearbox health condition is monitored through the amplitude of the fault-related sidebands in the lower frequency range of the motor current spectra. However, their practical implementation is challenged by the harmonics resulting from the structural properties of the electrical machines and the inherent system imperfections. This effect is even more severe in case of a drivetrain containing planetary gearboxes due to its more complex assembly. In this paper, the resonance residual technique, which investigates the spectrum region around the resonance frequency where rich fault information may occur, is applied for the first time to MCSA to detect planetary gearbox faults. This proposed approach is verified through both simulation and experiments. A lumped parameter model for an electromechanical drive train with an annulus gear tooth crack is simulated to investigate its effect on the stator current. For experimental verification, a similar 4-kW motor-planetary gearbox- generator test rig is used. The robustness of the proposed method is demonstrated through simulations of a nonlinear finite-element model and experiments under different operating conditions. Furthermore, the effectiveness of the proposed method to extract fault information over the existing methods is also shown.