Characterizing Surface-damage Progression of Spur Gears with Vibration and Oil Data
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Abstract
We present an empirical investigation of the gradual progression of surface damage in spur gears using two data sources: oil monitoring and vibration measurements. The test stand was equipped with a commercial magnetic filter, and a novel test process was developed to remove particles from the magnetic filter and suspend it in oil. In addition, oil samples were drawn periodically to analyze using LaserNet Fines. Both data-driven and classical vibration-based condition indicators were computed and compared to a simple, image-based feature quantifying of the surface condition with some of the indicators showing more than 80\% correlation. Oil analyses found relatively large particles in the particles collected from the magnetic filter.
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Gear, Surface damage, Vibration condition indicators, Autoencoders, Oil particle analysis
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