Frequency Energy Ratio Cell Based Operational Security Domain Analysis of Planetary Gearbox

Abstract

Planetary gearboxes (PGs) are significant transmission chains in industrial applications. Scientifically perceiving its operational security domain (OSD) is crucial for reliability analysis and preventive maintenance. Unfortunately, most security domain analysis methods discard the abundant information from the fault diagnosis indicator and measured data. To this end, this article proposes a frequency energy ratio (FER) based strategy to intelligently diagnose gear faults, identify the OSD and perform a reliability analysis of the OSD. The FER cell is constructed to consider multiple sideband numbers and bandwidth conditions. The optimal parameter pair among FER cells is determined by a novel distance measurement strategy, namely intra-inter class distance metric, which combines deep autoencoder and relatively max–minimum distance metric. The optimal FER can be conveniently applied to diagnose the remaining data. More importantly, the optimal FER with different fault-induced frequencies is picked to identify the OSD via minor training data. The failure probability of a large number of vibration data is calculated to verify the effectiveness of the OSD. Experimental results demonstrate that FER owns stronger robustness and diagnostic accuracy than the traditional sideband energy ratio. The proposed methods bridge the fault diagnosis and reliability analysis, which have a bright perspective in perceiving operational conditions from research and engineering fields.