Aerosense

A novel MEMS-based surface pressure and acoustic smart measurement system for wind turbines

Background

Wind energy is an important technology for achieving the UN Sustainable Development Goals and the EU Energy Strategy 2030. As the wind energy industry matures and wind turbines grow, there is an increasing need for cost-effective monitoring and data analysis solutions to understand the complex aerodynamic and acoustic behaviour of the blades, improve performance and reduce operating costs.

Project goals

The aim of this project is to develop, for the first time, a MEMS-based surface pressure and acoustic measurement system for wind turbines that is thin, non-intrusive, robust, modular, energy-autonomous, wireless, easy to install and cost-effective. The system will integrate novel embedded signal processing solutions, including artificial intelligence where appropriate, for on-board calibration and correction of measured variables, as well as a digital twin platform for effective data utilisation and value creation. Its modular and scalable design will enable wind turbine monitoring at a completely new scale.

The research objectives are:

• Research objective 1: Define system requirements for key customer groups.
• Research objective 2: Development of intelligent sensor correction and calibration procedures.
• Research objective 3: Design & development of a self-sustaining measurement system for the highest requirements defined in research objective 1.
• Research objective 4: Design & development of a digital twin platform including on-board signal processing.
• Research objective 5: Build, test & validate a prototype system (lab, wind tunnel & field).
• Research Objective 6: Publish a unique set of aerodynamic & acoustic field measurement data.
• Research Objective 7: Demonstrate the potential added value of the system.
• Research objective 8: Develop business cases & commercialisation plans.
• The AEROSENSE technology consists of (1) the blade system, (2) the base station system and (3) the digital twin on the cloud system, as shown on this pdf.

Project partners

This project is led by Sarah Barber from OST IET and is carried out together with the following partners:

• HSR IET (Dr. Sarah Barber): one PhD student, one research assistant.
• ETH Zurich Integrated Systems Laboratory (Prof. Luca Benini): One PhD student, one postdoc.
• ETH Zurich Structural Mechanics and Monitoring (Prof. Eleni Chatzi): One PhD student, one postdoc.

The members of the Advisory Board are:

• Enercon GmbH (Germany).
• GE Renewable Energy (Germany).
• EKZ Renewables (Switzerland).
• Brüel & Kjaer (Germany).
• Fraunhofer IWES (Germany).
• TU Delft (Netherlands).
• TNO ECN (Netherlands).
• NREL (USA).
• Danish Technical University (Denmark).

Please read more: www.aerosense.ai