Wind turbine blade at desert sunset with an Aerosense sensor patchWind turbine blade at desert sunset with an Aerosense sensor patch

Unlock wind turbine power performance with Aerosense blade-level intelligence.

0.5–3%

Additional annual energy production potential per wind turbine

<24 mo

ROI payback

1200 t

CO₂ avoided per turbine / yr

From blade aerodynamic measurements to boosted turbine power performance

01

Aerosense sensor patches

Wireless, thin, non-intrusive and self-powered patches bond directly to the blade surface, measuring aerodynamic pressure, vibrations and motion. No wiring and no structural modification to the blade is required.

02

Aerosense analysis engine

The analysis engine software infers aeroelastic performance metrics from the measured data: inflow conditions, aerodynamic loading and structural response.

03

Control parameter optimisation software

The rotor's aero-elastic performance is mapped to optimal site specific turbine controller set-points and parameters are tuned to the conditions each turbine experiences individually in the site, unlocking energy gains and reducing loads.

01 Aerosense Hardware

Pressure sensors

24 per node

IMU

3-axis accelerometer + 3-axis gyro

Sampling rate

100 Hz, fully synchronous

Communication

BLE 5, wireless

Dimensions

400 × 160 × 5 mm

Weight

320 g

Installation time

<10 min per patch

Field lifetime

12 months

Operating temperature

–30 °C to +60 °C

Maintenance

Zero

Pressure accuracy

± 50 Pa absolute

Time synchronisation

< 10 ms across patch
192

Pressure channels per blade

<10 min

Installation per patch

12 mo

Field lifetime / zero maintenance

How it works

8 Aerosense patches per blade

Typically installed at the root, middle and tip sections of each blade

Less than 10 minutes installation time per patch

No specialist required

1 gateway in the nacelle

Compact IP67 enclosure, installed in under 30 minutes

Wireless patch-to-gateway transfer

BLE 5 wireless communication, up to 100 m range

4G/LTE to cloud or on-premise

Secured data available within 30 minutes after measurements session end

02 – 

Analysis Engine Software

The Aerosense analysis engine software is a collection of physics-based and data-driven analysis modules that extract relevant features from the raw Aerosense hardware data to characterise rotor aerodynamic underperformance and detect available blade structural reserves.

01

Aerodynamics

1 / 5

Airfoil

Barometers

Cp < 0

Cp > 0

Relative wind

Reconstructs full Cp distribution from sparse sensor data.

_

Local pressure coefficient distribution along chord

_

Integrated sectional lift and drag force

_

Cross-sectional aerodynamic force

02

Blade kinematics

2 / 5

Flapwise

Edgewise

Axial

Blade translational and rotational deflection over time, flapwise, edgewise and axial

Estimates rigid-body motion and blade deformation from IMU data.

_

Rotor RPM

_

Blade azimuth position

_

Blade pitch angle

_

Blade twist

_

Rotational and translational blade deflection

03

Turbulent wind field characterisation

3 / 5

AEROSENSE

24.17 m/s · TI 10.2 % · window

GROUND TRUTH

23.33 m/s · TI 11.1 % · window

Free stream velocity over time, Aerosense inferred against ground truth

Infers local sectional inflow from sparse pressure measurements.

_

Angle of attack

_

Relative wind speed

_

Stagnation point position

_

Turbulence intensity

_

Turbulence length scale

_

Wind shear

04

Operational Modal Analysis

4 / 5

Analysis engine point cloud visualisation

Identifies dynamic properties from operational vibration response.

_

Blade natural frequencies

_

Blade vibration mode shapes

_

Damping ratios per mode

05

Structural loads

5 / 5

Identifies aerodynamically induced stress and strain states.

_

Spanwise cross-section loads

_

Reconstruction of stress and strain fields

_

Blade root loads

Wind turbine at dusk with airflow streamlines

03 – Aerodynamic Power Performance Optimisation

Aerodynamic Performance Optimisation

Every turbine experiences different turbulent wind conditions, but every turbine runs the same controller. This changes now.

Aerosense assesses site-specific aero-structural performance and inflow conditions of rotor blades and unlocks custom control policies to boost power production.

01

Annual Energy Production (AEP) Boosting & Revenue Maximisation

Increase the power output of turbines by retrofitting Aerosense to rotor blades and adapting controller to site-specific conditions.

+0.5–3%

Average AEP gain per turbine

Baseline

Aerosense

02

Mitigate site-specific aerodynamic underperformance

Deploy Aerosense on rotor blades to understand root causes of aerodynamic underperformance and identify corrective actions.

High pressure

Optimal

Aerosense

03

Power performance verification
and warranty provisions

Rapidly validate every individual turbine power performance on your site and reduce the risk of penalties during the warranty period and loss of revenue.

IEC guaranteed

Measured

Success Story:

Aerosense Campaign in Germany

Technician abseiling on a wind turbine blade above autumn forest

Retrofit installation of 8 Aerosense patches and a gateway on multiple blade sections in May 2026.

Installation time

3 hours

Data collection & reliability

>80%

Assessed the aerodynamic performance of the rotor blades and inferred the following quantities:

  • Aerodynamic power efficiency as a function of pitch and rotor speed
  • Operating angles of attack
  • Aerodynamic excitation forces
  • Margin to stall
  • Time the blade spends in stall
  • Blade deflection and twist
  • Rotor modal frequencies, damping and shapes
  • Potential control optimisation strategies to boost power production

About RTDT

RTDT was founded in 2022 as a spin-off company of ETH Zurich, Switzerland’s leading research institute, with the mission to optimise the performance of wind turbines with the innovative Aerosense technology.

Backed by

Awards

Supported by

Team

We are a diverse team of experienced wind energy industry veterans and domain experts in aerodynamics, structural mechanics, software and electronics.

Dr. Imad Abdallah

Dr. Imad Abdallah

CEO & Co-Founder

Aris Mukherjee

Aris Mukherjee

COO & Co-Founder

Dr. Konstantinos Tatsis

Dr. Konstantinos Tatsis

Chief Science Officer & Co-Founder

Dr. Julien Deparday

Dr. Julien Deparday

CTO

Yuri Jean Fabris

Yuri Jean Fabris

VP of Engineering

Dr. Amirhossein Moallemi

Dr. Amirhossein Moallemi

Senior Hardware Engineer

Denis Mikhaylov

Denis Mikhaylov

Embedded Systems Engineer

Marios Panourgias

Marios Panourgias

Data Scientist

Dr. Aananthy Sarma

Dr. Aananthy Sarma

Test Engineer

Odysseas Kyparissis

Odysseas Kyparissis

Data Scientist

Yan L'Homme

Yan L’Homme

Machine Learning Engineer

Raphael Fischer

Raphael Fischer

Senior Electronics Engineer

Dr. Konstantinos Agathos

Dr. Konstantinos Agathos

VP of Algorithms

Gaëlle Le Texier

Gaëlle Le Texier

Mechanical Engineer

Marcus Lugg

Marcus Lugg

Backend Engineer