A comparative study of gear fault diagnosis methods based on the motor drive system

In the gearbox-based electromechanical system, some electrical signals, such as the electromagnetic torque and the motor current, can track the pulsations of the load torque, which contributes to the fact that the motor can be considered as a non-destructive sensor to diagnose gear faults. Firstly, this paper establishes an integrated electromechanical model of the motors and gear drive system. Then, the theories of the electromagnetic torque signature analysis (ETSA) and the motor current signature analysis (MCSA) for fault diagnosis are analyzed and verified through simulation. It can be seen that the electromagnetic torque, which is free of the main frequency, can reflect the failure information more intuitively. Also, the fault features in frequency domain are more obvious than those in time domain. Finally, the performances of these two methods are compared at different speed and load torque conditions by experiment. The results show that both methods are influenced by speed and load torque. It would be better to perform fault diagnosis under low speed and heavy load. However, ETSA is effective in a wider range than MCSA.