Predictive maintenance for gearboxes
Predictive maintenance for gearboxes combines vibration analysis and oil analysis to detect gear-tooth wear and cracking, bearing defects and lubrication problems — protecting high-torque, high-value drivetrains where a failure is expensive and slow to repair.
Why monitor gearboxes
Gearboxes are expensive, often have long lead times, and sit in critical drivetrains. Gear and bearing faults develop gradually and show clearly in vibration spectra and oil debris, so a monitored gearbox can be planned for overhaul rather than failing mid-production.
Common failure modes
- Gear-tooth wear, pitting and scuffing
- Tooth cracking and breakage
- Bearing wear and defects
- Lubrication breakdown and contamination
- Misalignment and overload
Which monitoring techniques fit
- Vibration analysis (gear-mesh frequencies and sidebands)
- Oil analysis for wear metals and particle counts
- Oil-debris sensors on critical units
- Temperature monitoring
What the data shows
Growing sidebands around the gear-mesh frequency indicate localised tooth damage; rising wear-metal levels in oil confirm gear or bearing wear. Together they pinpoint the component and the severity.
Related guides
Software that helps
Augury
Machine health monitoring for rotating equipment using vibration and AI.
AVEVA Predictive Analytics
Early-warning analytics for critical process and power assets.
Siemens Senseye Predictive Maintenance
Scalable predictive maintenance that learns from existing condition data.