We are looking for £20,000 grant funding to complete our proof of concept validation and move from TRL 5 to TRL 6.
TorqueScope detects wind turbine drivetrain faults by analysing existing SCADA data — no new sensors, no hardware, no historical failure data required. The platform applies the Ab Astris Lomb-Scargle periodic signal detection framework, originally developed for variable star discovery with NASA TESS photometry, to temperature and operational sensor streams from turbine SCADA systems.
The core insight: physics-constrained systems — rotating machinery, tidal constituents, stellar orbits — produce periodic signals with coefficient of variation (CV) below 2%. Faults disrupt that stability. TorqueScope detects the disruption before it becomes a failure.
The Levenmouth Demonstrator Turbine is the only publicly accessible wind turbine dataset with a categorised fault alarm log. Every other public dataset — including the CARE benchmark, which carries the strongest ground truth labels of any open dataset — records turbine stop events, not fault categories. Levenmouth lets TorqueScope measure probability of detection per fault type: gearbox, bearing, yaw system, pitch system. That is the number operators and insurers ask for.
| Dataset | Turbines | Fault log | POD by category |
|---|---|---|---|
| CARE benchmark | 36 | Stop events only | ✗ |
| Kelmarsh / Penmanshiel | 25 | Stop events only | ✗ |
| Hill of Towie | 21 | Stop events only | ✗ |
| Levenmouth | 1 (7MW) | Categorised faults | ✓ |
| Milestone | Deliverable | Gate | Timeline |
|---|---|---|---|
| M1 Data ingest | Levenmouth 574-channel SCADA ingested, format validated | Zero-code-change format test passes | Month 1 |
| M2 POD validation | POD per fault category measured against alarm log | POD ≥ 70%, mean lead time ≥ 24h | Month 2–3 |
| M3 Technical report | Validation report for ORE Catapult, suitable for funder submission | Report accepted by ORE Catapult innovation lead | Month 3 |
| M4 Pilot prospectus | Commercial pilot pack for operator outreach | First meeting with Banks Renewables or Fred Olsen Renewables | Month 4 |
Sequencing logic: Banks Renewables as the reference customer (accessible, innovation-receptive, no OEM lock). Greencoat UK Wind as the institutional prize (1.8GW+, independent O&M, institutional buyer). ORE Catapult as the parallel credibility accelerator — LDT validation strengthens all three routes simultaneously.
Research & innovation body, Levenmouth access, grant pathway
Independent operator, onshore UK, accessible procurement
Independent, onshore & offshore, not OEM-captive
Largest UK wind fund, 1.8GW+, institutional buyer
Norwegian state-owned, significant UK onshore portfolio, innovation appetite
Major independent developer-operator, technology-forward, internal O&M
SCADA software provider, white-label integration opportunity
UK addressable market (TRL 7–8): Approximately 11,000 operational wind turbines in the UK. At a conservative £8,000 / turbine / year SaaS licence on 10% penetration, that represents an annual recurring revenue ceiling of ~£88M in the UK alone.
Global addressable market (TRL 9): 450,000+ commercial wind turbines globally. The total addressable market for SCADA-based condition monitoring — a segment currently dominated by OEM-locked proprietary systems — is estimated at $2.1B annually and expanding as turbine counts grow and offshore decommissioning risk increases. Zero-shot, hardware-free detection is a structural advantage in the 80% of the global installed base where independent CMS coverage is absent.
TorqueScope is a cold-start capable, hardware-free wind turbine fault detection platform. Its periodic signal layer begins scoring from day one with no historical failure data; its normal behaviour model calibrates over the first 60 days. No competitor offers useful output without 12-24 months of baseline collection. The Levenmouth dataset is the missing piece: ground truth at fault-category resolution, on an offshore-class turbine, accessible through ORE Catapult. £20,000 buys the data, the validation, and the first commercial conversation - for a platform built to work anywhere on earth.
The premium end of the wind O&M market is already served - expensively, by OEM-locked systems with £5-15k hardware installations per turbine and contracts that assume the operator has a maintenance budget, a service team, and years of historical failure data. TorqueScope's real opportunity is the 80% of the global installed base that has none of those things.
The delta is not marginal. It is the difference between having early warning and having nothing.
In mature markets - UK, Germany, Denmark - an unplanned turbine failure is expensive but manageable: a mobilised crew, a spare part, a few weeks of lost generation. In resource-constrained markets, the same failure can mean months of downtime, lost grid capacity in a system with no slack, and communities returning to diesel generation. The economics of prevention are not just stronger - they are transformative.
Grid penetration of wind is rising but O&M infrastructure is nascent. A single large turbine failure on a constrained grid removes capacity that cannot be quickly replaced. TorqueScope's Kenya mode - already built, validated on Lake Turkana, Kipeto and Ngong Hills climate data - demonstrates the platform's readiness for this context.
Kenya mode builtIndia's wind sector is adding capacity faster than its O&M workforce is scaling. The gap between turbine installation and effective condition monitoring is widening. A zero-hardware, zero-training-data system is not a premium product here - it is the only viable product.
high growthSmall island developing states - Caribbean, Pacific, Indian Ocean - are deploying wind as primary generation. A single turbine failure on a 4-turbine island installation is a grid emergency. The economics of early warning here are not about optimising an O&M budget. They are about keeping the lights on.
grid-critical