EAR-MP-2025

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Title

Gearbox Fault-Severity & Confidence Estimation

Summary

Develop a model that classifies gearbox pitting severity (11 grades) and outputs prediction confidence for previously unseen speeds & torque. The training set spans 15 rotational speeds × 6 torque levels and covers seven health states (healthy + six faulty), whereas the hidden test/validation sets extend to 18 unseen speeds and the full eleven-level degradation spectrum. This deliberate coverage gap simulates real PHM practice and demands robust generalization to fault levels and conditions absent during training. Leaderboard scoring combines a proximity-based ordinal penalty with a confidence factor, rewarding accurate, well-calibrated, and trustworthy forecasts.

Deliverables

• Model & code (GitHub)
• 4-page short paper
• Presentation materials
• Demo video

Expected number of team members

4 students

Expected duration in month

5 months

Data sets

• Training and test datasets are available at Data download
• Around 6 GB data set: 3-axis vibration, 15 RPM × 6 torque conditions (train) + extended test/valid sets, CSV/NPY archives.

GPU cloud server

CPU-only baseline feasible in < 2 h

Additional Information