Gear Tooth Fault Detection in Servo Motor Transmission Chain Using the Built-In Encoder of Servo Motors
Jiawei Fan, Yu Guo, Jing Na, Xingchao Yin
Abstract
Gear tooth fault detection typically requires the installation of additional sensors such as vibration and acoustic emission sensors. However, this approach usually has limitations such as installation positions, additional sensor costs, and cable connections in certain operational scenarios. To address these issues, this paper proposes an alternative method for gear tooth fault detection by utilizing the signals from the built-in encoders of servo motors, eliminating the need for external sensor installation. Firstly, the angular pulse train generated by the encoder is obtained via transmission cables, and a high-speed counter is employed to record the time series corresponding to the rising edges of the encoder output pulse train. Subsequently, the instantaneous angular speed (IAS) signal is estimated from the encoder signal, and gear tooth fault related features can be extracted in the angular and order domains. Finally, the effectiveness of the proposed strategy is validated through examples of gear tooth faults in a planetary gearbox and an RV reducer.