Fault detection of RV reducer cycloidal gear under robot working conditions based on optimization improved envelope spectrum sideband energy ratio

Abstract Under industrial robot operating conditions, the cycloidal gear in the rotary vector (RV) reducer in the robot joint runs in a compound rotation motion with a low-speed and incomplete cycle, which complicates the fault detection for the cycloidal gear. Until now, no effective detection method for the cycloidal gear tooth fault under industrial robot operating conditions has been reported. Consequently, a method based on optimization improved envelope spectrum (IES) sideband energy ratio is proposed in this paper. Firstly, encoder signals are acquired and used to estimate the instantaneous angular speed signals, which are then separated into two sets of data based on rotation directions. Then, the data corresponding to the approximately stable speed is truncated and connected to form a constructed signal. Next, the coherence of the constructed signal is calculated using the fast spectral coherence algorithm. Subsequently, the IES sideband energy ratio is used as the objective value, and a global optimization algorithm is employed to determine the integration frequency band of the IES. Finally, the IES of this frequency band is calculated to obtain the fault-related order characteristics. An RV reducer test rig was used for the experiment, and the analysis results from the proposed approach, cyclic spectral coherence, and IES via feature optimization-gram were contrasted. Experiment results show that the proposed method is valid for the detection of tooth faults in the cycloidal gear of the RV reducer in robot operating conditions.