research
Nine Aircraft Faults Become a 920-Million-Step Benchmark
Pneuma opens real in-service bleed-air time series across four commercial-aircraft types, tied to verified maintenance logs.
Summary
Pneuma opens real in-service bleed-air time series across four commercial-aircraft types, tied to verified maintenance logs.
Predictive-maintenance research is often built on private or synthetic data. Pneuma contributes more than 920 million multivariate time steps from in-service commercial aircraft, spanning four aircraft types and nine verified bleed-air fault scenarios. It defines forecasting, supervised classification and unsupervised anomaly-detection tasks, then evaluates more than 25 models on nine subsets. Strong contemporary systems still struggled with subtle fault signatures, while more in-context examples and multivariate inference helped. The benchmark's labels come from real maintenance logs, but it covers one subsystem family and does not itself certify any model for operational aviation decisions.
Why it matters
Pneuma opens real in-service bleed-air time series across four commercial-aircraft types, tied to verified maintenance logs.
Limits and context
- The benchmark's labels come from real maintenance logs, but it covers one subsystem family and does not itself certify any model for operational aviation decisions.
Key claims
Pneuma opens real in-service bleed-air time series across four commercial-aircraft types, tied to verified maintenance logs.
Qualification: The benchmark's labels come from real maintenance logs, but it covers one subsystem family and does not itself certify any model for operational aviation decisions.
Evidence: source-2026-10-29-007
Sources
- arXiv preprint 2610.37563, original v1arXiv · primary research
Corrections
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