Know how every blade is behaving, not just how it looks.
Continuous optical sensing and modal analysis across all three blades, so a change in structural behaviour shows up as a number long before it shows up in an inspection image.
Blade failures are expensive, and largely avoidable
Blades are among the most expensive and least accessible components on a turbine. Failures, from pitch bearing degradation to structural fatigue, cost operators millions in unplanned downtime and emergency mobilisation. Yet most blade monitoring still relies on periodic visual inspection: costly, weather-dependent, and unable to catch the early-stage change that precedes a serious failure.
Offshore the problem compounds. Access is restricted, weather windows are narrow, and every vessel deployment carries a large fixed cost. By the time a problem is visible, the damage is usually well advanced.
Inspection sees a surface
It documents what the outside of the blade looks like at one moment. It cannot tell you whether the structure underneath is stiffer or softer than it was three months ago.
Intervals are set by calendar
Scheduled inspection is the same for a blade that is quietly changing and one that is not, which means effort goes where the calendar says rather than where the evidence points.
Alarms without context are ignored
A vibration change can come from the structure or from the operating point. Without wind speed, rotor speed and load in the picture, an alert system trains its users to stop reading it.
Measure all three blades, and compare them with each other
Optical vibration and strain sensing measures the dynamic behaviour of the blades continuously. Modal analysis extracts frequency and damping characteristics; the interesting signal is not any single number but the divergence between blades that should be behaving identically.
Optical sensing
High-sensitivity fibre optic vibration and strain sensing, immune to electromagnetic interference, which matters in a structure where lightning is an explicit design case. No electronics inside the blade and no metal path to the tip.
Modal analysis and anomaly detection
Frequency drift and vibration energy, always compared at the same rotor speed. Pairwise correlation across the three blades surfaces the asymmetry that developing damage produces.
Fused with operational data
Turbine control data and environmental conditions provide the context that separates a genuine structural change from normal operational variation. This is what keeps the false alarm rate low enough for the output to stay credible.
An indicator of how far a blade has moved, not a diagnosis
What the system delivers
- Continuous structural health monitoring, without a scheduled inspection window.
- A score per blade, computed at consistent operating conditions rather than on raw comparison.
- Three references: the blade's own history, its two siblings on the same turbine, and peers of the same type in the same farm.
- Severity classification and a recommended action, delivered through a dashboard your own engineers can interrogate.
- Fleet view: which turbine needs attention first, and on what evidence.
What it does not do
- It does not classify the damage. It tells you that behaviour has changed, not what the defect is.
- It does not replace inspection. It tells you where inspection is worth spending.
- It does not issue a go or no-go. That stays with the people who inspect and certify.
- Progressive damage gives warning. A sudden overload failure does not, and we would rather say so than let the impression stand.
At a glance
- Status
- Operational, monitoring wind turbine blades in continuous deployment.
- Sensing
- Optical vibration and strain sensing. High sensitivity, immune to electromagnetic interference, no modification to the blade structure.
- Platform
- FleetSense, our production sensing and data platform, running continuously for around three and a half years across 66 fibre optic sensors.
- Data approach
- Fusion with turbine control data and environmental conditions, so that operating point is accounted for before anything is flagged.
- Programmes and consortia
- AIRTuB ROMI, ReliaBlade2 NL, PhotonDelta, OWIC, and collaborations including Eneco, Vattenfall, Shell and TNO.
- Best fit
- Asset owners and operations teams responsible for availability across a fleet, onshore or offshore, and turbine manufacturers looking to integrate monitoring into their own offering.
A blade repair already scheduled?
Continuous monitoring answers how a blade is behaving over time. A repair campaign is a different question: what state the blade was in beforehand, and what happened to it during the dismount, transport and lift. BladeTrace covers that specific window, and the two work together on the same installation.
Which turbines are you least sure about?
The useful first conversation is usually about one site: what you already measure, what your inspection interval costs you, and whether behaviour-based monitoring would change any decision you currently make on a calendar.
