Research on the Identification Method for Planetary Gear Damage in Industrial Robot Gearboxes Based on Acoustic Emission Signal Analysis

In response to the need for identifying planetary gear damage in industrial robot gearboxes, this study proposes a damage feature extraction method based on acoustic emission (AE) signal analysis. Firstly, an experimental platform was established, and AE signals were collected under the condition of both normal and planetary gear damage in the gearbox. Next, the signals were decomposed into node signals at different frequency bands using a three-level wavelet packet decomposition(WPD), and the node signals containing the most significant damage-related information were selected based on kurtosis values and spectral entropy. The selected node signal was then used to reconstruct the AE signal. Subsequently, the Hilbert envelope demodulation technique was applied to extract the modulated components from the reconstructed signal, and the envelope spectrum was analyzed to reveal sideband features associated with gear damage. Finally, the relative sideband strength (RSS) was employed for quantitative analysis of the sidebands, further validating the correlation between the damage state and spectral energy distribution. Experimental results demonstrate that the proposed method shows strong accuracy and robustness in identifying planetary gear damage in industrial robot gearboxes, providing effective technical support for fault diagnosis and health monitoring of equipment.