Moving from fixed-interval diver inspections to a prioritised risk queue
Predictive corrosion monitoring for submerged monopile foundations across several wind farms
These figures match the published metrics on the Predictim Corrosion Solution product page — this walkthrough is a composite scenario, not a specific engagement.
Predictive corrosion monitoring for submerged monopile foundations across several wind farms
Segment: Offshore wind corrosion monitoring
Diver and ROV inspection campaigns are expensive and weather-dependent, so operators default to a uniform inspection interval across every structure. That treats a monopile in mild, well-oxygenated water the same as one in a local corrosion hot spot — spending inspection budget evenly instead of where risk is actually concentrated, and leaving no early signal between scheduled visits.
How the approach works
Prediction, not just monitoring
Machine-learning models — grounded in the submerged-steel corrosion research from the SOCORRO-Interreg programme — predict uniform corrosion rate for unprotected steel before physical decay is visible.
Multi-sensor telemetry, continuously
pH, conductivity, dissolved oxygen, and temperature stream into a local water-corrosivity index in real time via a developer API, rather than a snapshot taken during a scheduled visit.
A risk matrix, not a flat schedule
Telemetry history maps into a risk matrix per structure, so anode replacement and maintenance budget go to the monopiles that actually need it first.
Offshore-specific models
Pre-configured models for wind turbine monopiles and sheet piles mean the risk scoring reflects the actual asset type, not a generic submerged-steel default.
Reallocating inspection and anode-replacement budget by predicted risk, instead of spreading it evenly across the fleet, is the core shift — the same one the underlying SOCORRO-Interreg research programme set out to enable for submerged steel infrastructure generally.
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