Aerosense

Rapid, multilocational and cost-effective aerodynamic, vibrational and acoustic data capture on turbine blades

Optimising monitoring & diagnostics of wind turbine blades

Civil structure designers and operators often struggle with capturing precise aerodynamic, vibrational, and acoustic data across their assets. Traditional methods either lack accuracy or are costly and intrusive.

Enter our solution: the first to simultaneously measure these parameters at multiple locations, rapidly and accurately. It's autonomous, simple, quick, and non-intrusive, offering a cost-effective way to optimize large-scale civil engineering structures. Experience the future of precision engineering today.

Get involved

We are looking for a pilot project and manufacturing partners – get in touch if you are interested.

Product overview

Modular, autonomous and heterogeneous multi-sensor node in one package

Low-power electronics, Bluetooth data transmission, and autonomous power management via a solar panel, all integrated into a thin 3D printed housing

Cloud-based digital twin with inverse and forward problem solvers to predict and infer relevant flow quantities

Integrated with the RTDT state-of-the-art suite of models and algorithms for structural monitoring & diagnostics

Can be distributed along the span of the blade in an autonomous, easy, quick, non-intrusive and cost-effective unit

Simply glue the Aerosense node on the external surface of the wind turbine blade, and it is good to go

Absolute aerodynamic surface pressure from 40 barometers for each blade section

Differential pressure at the leading edge from 5 differential pressure sensors

Vibrations from a 6-DOF IMU unit

Blade surface temperature

Acoustics from embedded microphones at the trailing edge

Sampling rate: 100Hz (kHz range is possible for microphones and differential pressure sensors)

Revolutionise your wind turbine inspections with Aerosense

Cut down on high costs and limited data from traditional inspection methods. With Aerosense, there's no more reliance on drone-based inspections (~500 CHF per flight per turbine) or rope access inspections (~3000 CHF per turbine per day). Forget about the limitations of embedded fiber optic strain sensors that only measure strain and are too expensive.

Aerosense offers the potential to replace nacelle-mounted Lidar systems for wind inflow characterization on the rotor plane. Our unique selling point? Aerosense enables users to access a wide range of aerodynamic and structural monitoring and diagnostic use cases for wind turbine blades. All from a single low-energy, wireless, non-intrusive multi-sensor node. Choose Aerosense. Choose efficiency.

What it can do

The entire digital twin chain is operational

Deliver and display measurement data from the wind turbine on the dashboard

Improve aero-acoustic models, tools and designs

Assess sound pressure levels and infer the angle of attack from measurement data

Detect and classify surface damage such as Leading Edge Erosion (LEE)

A separate simulation framework trains ML models for classifying LEE.

Detect and classify structural faults

Various models can be applied directly to aerodynamic pressure time series data to detect structural faults

Reconstruct flowfields

For a snapshot of the pressure distribution around an airfoil, determine the surrounding steady pressure and velocity fields. At the same time, determine free stream conditions (velocity, turbulence, AoA)

How it was developed

Aerosense is based on the technology developed within the BRIDGE Discovery project «Aerosense»*, which finished on 30.04.2023. The project was lead by Sarah Barber at the Eastern Switzerland University of Applied Sciences (OST), one of our Scientific Advisory Board members.

Wind Energy Innovation Division at the Eastern Switzerland University of Applied Sciences

Dr. Sarah Barber

Project manager

Dr. Julien Deparday

Postdoctoral researcher

Dr. Yuryi Marykovskiy

PhD student

Chair of Structural Mechanics and Monitoring at ETH Zurich

Prof Dr. Eleni Chatzi

Head of laboratory

Dr. Imad Abdallah

Postdoctoral researcher

Gregory Duthé

PhD student

Center for Project-Based Learning at ETH Zurich

Dr. Michele Magno

Head of laboratory

Dr. Tommaso Polonelli

Postdoctoral researcher

Hanna Müller

PhD student

Monitoring as a Service

The RTDT software supports owners, operators, service providers and OEMs throughout their journey into monitoring and diagnostics for more reliable and profitable wind turbine fleet

Research

We conduct fundamental, long-term R&D toward the creation of safe and reliable wind turbines

Aerosense

Optimising monitoring & diagnostics of wind turbine blades

Get involved

Product overview

Revolutionise your wind turbine inspections with Aerosense

What it can do

The entire digital twin chain is operational

Improve aero-acoustic models, tools and designs

Detect and classify surface damage such as Leading Edge Erosion (LEE)

Detect and classify structural faults

Reconstruct flowfields

How it was developed

Wind Energy Innovation Division at the Eastern Switzerland University of Applied Sciences

Dr. Sarah Barber

Dr. Julien Deparday

Dr. Yuryi Marykovskiy

Chair of Structural Mechanics and Monitoring at ETH Zurich

Prof Dr. Eleni Chatzi

Dr. Imad Abdallah

Gregory Duthé

Center for Project-Based Learning at ETH Zurich

Dr. Michele Magno

Dr. Tommaso Polonelli

Hanna Müller

Monitoring as a Service

Research

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