TorqueScope identifies emerging faults in wind turbines up to 59 hours before breakdown - using only the SCADA data you already collect. No new sensors. No historical failure data. No ML team required.
Two independent detectors, each grounded in physical principles, must agree before an alarm is raised. Neither requires fault examples. Neither requires domain expertise to deploy.
A 7-day sliding window over temperature sensors is decomposed into its frequency components. Healthy drivetrain signals show stable periodic structure - rotor harmonics, diurnal thermal cycles, mechanical resonances. Deviation from this baseline triggers the heuristic score.
Expected temperature is modelled as a function of power output and ambient conditions across a 200-bin operational grid (20 × 10 bins). Residuals from this physics-informed lookup reveal anomalous thermal behaviour invisible in raw sensor streams.
When both detectors agree, confidence is amplified. A criticality counter accumulates evidence over time, rising on anomaly readings and decaying otherwise. Single-detector signals are suppressed by 50%, converting noise into structured forewarning.
Validated against the CARE benchmark - 95 datasets, 3 anonymised wind farms, ground-truth fault timestamps confirmed by maintenance personnel. Lead time measured from first TorqueScope alarm to documented fault onset.
| # | Fault Description | Farm | Sensors | Lead Time |
|---|---|---|---|---|
| 01 | Gearbox failure | Farm A - Onshore, Portugal | 86 | 32.3hours |
| 02 | Yaw grease pump failure | Farm C - Offshore, Germany | 957 | 50.0hours |
| 03 | Gear oil pump coupling defect | Farm C - Offshore, Germany | 957 | 59.3hours |
| 04 | Main bearing damage | Farm B - Offshore, Germany | 257 | 29.5hours |
41 turbines across Kelmarsh, Penmanshiel, and Hill of Towie. Real SCADA from three UK wind farms — no synthetic data, no simulation.
Watch TorqueScope detect a gearbox failure 59.3 hours before confirmation. Four real fault scenarios, streaming in real time.
15 wind farms across 10 countries. NASA POWER climate data, Weibull analysis, generation projections, and side-by-side comparison.
Hybrid score across the prediction window for Farm A, Event 10. The criticality counter crosses threshold 72 a full 32.3 hours before the documented fault onset.
The Lomb-Scargle periodogram at TorqueScope's core is not wind-specific. Ab Astris validates the same frequency-domain approach across six independent physical domains — proving that physics-constrained periodic signals produce stable, detectable signatures without domain-specific training.
Validated on oceanographic tides (6 NOAA stations, 24/24 constituents detected), industrial bearings (CWRU dataset, 0.008% CV), volcanic tremor (4 volcanoes), structural resonance (CESMD buildings + Z24 bridge), and astronomical variable stars — with negative controls on cryptocurrency, heart rate variability, and sunspot data confirming the CV discriminator rejects non-physics-constrained signals.
Read the paper on Zenodo →CMS installations require hardware procurement, site visits, and years of failure data to train on. TorqueScope connects to your existing historian in days.
| Capability | Typical CMS | TorqueScope |
|---|---|---|
| New sensors needed | Yes - €5–15K/turbine | None |
| Historical fault data | Required | Not required |
| Deployment timeline | Months | Days |
| Viable on small farms | Uneconomic | Yes |
| Alarm interpretability | Black-box | Sensor-level |
| Max validated lead time | Varies | 59.3 hours |
No contract, no hardware order, no ML team. Validated on three real wind farms across two countries. Operational within days from your existing SCADA historian.