Wind turbine blades, bridges, hydrogen tanks and aerostructures increasingly remain in service beyond their design life and under more severe loads than planned.
In composites, impact damage and the resulting delaminations are often not visible on the surface (BVID). Periodic inspections cannot track their growth.
Unplanned downtime, emergency repairs and structures oversized by conservative safety factors.
At the heart of the patent is a flexible, removable printed circuit with seats for interchangeable piezoelectric transducers, connected to a microcontroller module that processes the signals autonomously.
The device works in active mode, interrogating the structure on demand, or in passive mode, listening to record events such as impacts.
One transducer emits a burst of ultrasonic waves that travels through the structure; the others receive the signal in a pitch-catch configuration.
The microcontroller acquires and pre-processes the signal of every actuator–receiver path, directly on the device.
Damage indices, numerical models and AI/ML algorithms estimate the presence, position and extent of damage.
The damage map reaches a smartphone or dashboard: intervene where needed, when needed.
We handle the whole chain: sensor selection and integration, acquisition electronics, data management and visualisation of results. Combining several quantities makes diagnosis more robust under real operating conditions.
Coin-sized piezoelectric transducers excite and receive guided waves that propagate through the material. They detect cracks, delaminations and internal damage, even in complex composite or metallic structures.
Measures strain and temperature profiles along the fibre to identify localised anomalies and load variations. It is the next extension of the patch and the subject of an upcoming patent application.
Inertial sensors and other contextual measurements describe vibrations, dynamic response and transient events, complementing static and quasi-static measurements.
Proprietary data-fusion and diagnostic algorithms, supported by numerical models, are designed to separate the effects of damage from those of temperature and load. Explainable AI methods make the results interpretable for decision-makers.
Sensor performance matters, but so does how easily it can be installed, used and replicated across a fleet of assets.
The flexible patch conforms to curved surfaces and stiffened panels.
Fast installation, reduced downtime, no cable bundles running to an acquisition rack.
On-site tests and immediate results on a smartphone, even in hard-to-reach areas.
Same platform, repeatable installations, data comparable across assets.
Objective reports and indicators for quality, HSE, audits and compliance: every intervention is justified by measured data.
Numerical models and digital twins work alongside machine learning: not just a classification, but an interpretable estimate of the structure’s condition and how it is evolving.
The technician starts a measurement over Bluetooth and sees the damage map directly on the phone. Data can feed a dashboard that keeps the asset’s history.
Tell us about your case: together we will design a pilot with measurable KPIs.