Turning anomaly detection into decision certainty
When monitoring detects a problem — who confirms it?
ALIDA brings physical validation into wind turbine operations, closing the gap between data and decision.
Tested in real industrial environments · Rotor & blade focus · OEM-relevant workflows
Detection is not validation
Monitoring platforms are good at detecting anomalies. But they often fail at answering the only question that matters:
Is this real — and what should we do about it?
This leads to decisions based on incomplete information.
SCADA signals without structural validation
Data shows deviations but no physical confirmation of what's happening at the rotor.
Unclear root causes
Anomaly signals without physical interpretation leave teams guessing at what's actually wrong.
OEM escalations
Without validated evidence, escalations to OEMs lack the data needed for swift resolution.
Costly and unfocused inspections
Inspections triggered without structural context waste time and budget on broad, undirected checks.
This gap creates delay, cost, and decision uncertainty.
Today's systems stop at detection
SCADA and performance analytics can surface anomalies, but they rarely provide a structured way to validate them physically at component level — especially on rotor and blade systems.
Digital Detection
SCADA · CMS · Analytics Platforms
Physical Reality
Rotor · Blades · Structural Behavior
ALIDA is designed for this missing layer.
A validation layer for when monitoring is not enough
ALIDA acts as a physical validation endpoint integrated into existing monitoring workflows.
Capture
Laser + video sensing. No turbine modification required.
Analyze
Rotor dynamics. 1P / imbalance / anomaly interpretation. AI-assisted signal analysis.
Validate
Structural confirmation. Actionable insight for O&M and engineering teams.
From anomaly signal to structural insight
Used to confirm rotor imbalance and support targeted intervention decisions.
- 1P harmonic extraction
- Blade-specific bias estimation
- Evidence for inspection prioritization
From signal anomaly → to physically validated structural insight
Why it matters
When anomalies are not validated, maintenance becomes reactive, inspections become broader and more expensive, decisions slow down, and confidence in analytics decreases.
Without ALIDA
- Reactive maintenance driven by uncertain signals
- Broader, more expensive inspections
- Slower decision-making across the chain
- Decreased confidence in analytics output
With ALIDA
- Faster, evidence-based decisions
- More targeted inspections with structural context
- Reduced uncertainty in maintenance planning
- Better coordination across monitoring, engineering, and O&M
Designed for real-world integration
Deployable on operating turbines, without shutdown, modification, or disruption.
Works without:
- Turbine downtime
- Structural intervention
- Restricted access requirements
Integrated as a validation layer on top of existing SCADA and analytics systems.
When ALIDA is used
Unclear SCADA anomaly
When monitoring flags something but the root cause is uncertain.
Repeated alerts without root cause
Persistent alerts that don't resolve and lack structural explanation.
Before OEM escalation
Get physical evidence before escalating to manufacturers.
Before costly inspection campaigns
Validate before committing to expensive, broad inspection programs.
Not another monitoring system
Monitoring detects anomalies.
ALIDA confirms what is actually happening.
A decision validation layer.
Built in industrial context
Developed around real industrial rotor analytics problems.
Activities explored in OEM-relevant environments, including Vestas-related contexts.
Built for complex industrial systems
Founder
AI Architect with experience across industrial AI, IoT, and real-world deployment.
Experience spanning production-grade AI systems, industrial analytics, and technical delivery in demanding contexts.
Selected for Free Electrons shortlist
We are currently exploring pilot opportunities with utilities and partners.