Gear tooth surface damage fault detection using induction machine electrical signature analysis

Abstract

The aim of the present work is the diagnosis of tooth surface damage fault in gears using the induction machine electrical signature analysis. The condition monitoring of gears is a crucial task due to its importance in the mechanical power transmission in industrial, aerospace and automotive applications. The vibration analysis has been commonly used as an effective tool for gear fault diagnosis in several studies. The gear torsional vibration effect in the stator current and the estimated electromagnetic torque has been previously studied based on the observation of gear mechanical characteristic frequencies in the spectrum of the load torque. This paper investigates the profile generated by a gear tooth surface damage fault in the load torque. It will be shown that the periodic behavior of this particular profile produces fault-related frequencies in the stator current and hence harmonics namely integer multiple of rotation frequency in the instantaneous frequency of the stator current space vector and the estimated electromagnetic torque. The obtained results show a possible non-invasive gear tooth surface damage fault detection with a fault sensitivity comparable to the one obtained with invasive methods. A set-up based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage gear has been used for this purpose.