Research

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

Do you know the health state of your wind farm assets?

This is a question every owner of wind farms and manufacturer of wind turbines should ask themselves. Unplanned costs due to failures, make up more than half of total maintenance costs, and the simple truth is: only a reliable plant earns money. Continuous and automated online monitoring, diagnostics, and prognostics will be the main tools to lower maintenance costs and optimize the power and structural performance of wind turbine fleet.

RTDT makes condition and structural health monitoring of wind energy assets effortless for engineers, managers, and non-experts. Our technology stack lowers the barriers to entry to users and enhances their capabilities to deploy scalable research-based state-of-the-art models to extract deep interpretable and actionable insights, in minutes, in a no-code environment.

Towards this end, RTDT conducts fundamental, long-term R&D toward the creation of safe and reliable wind turbines.

The RTDT Research Affiliate Programme

The RTDT Research Affiliate Programme brings together researchers with real data and challenges from the industry in order to create state-of-the-art open-source models and analysis tools for wind turbine Structural Health Monitoring (SHM).

For this, we use WeDoWind, which is a framework for bringing asset owners together with researchers and model developers in a "win-win" situation, operated by Sarah Barber at the Eastern Switzerland University of Applied Sciences and co-founded by RTDT's CEO, Imad Abdallah.

The idea is that asset owners get easy access to state-of-the-art data analytics and model developers get access to relevant asset data to train and validate their models. It is based on industry-provided challenges, which are coordinated through digital spaces. Multiple digital spaces form branch-specific ecosystems of collaborators.

The RTDT Research Affiliate Programme provides members with:

Open Science

Participation in an Open Science process based around WeDoWind Challenges. The regular online moderated workshops allow the challenges to be solved and discussed together, help and motivate members to collaborate and work together, provide easy access to people at RTDT, and allow problems to be solved quickly and new ideas to be developed. “Offline” options available for people who cannot attend (using the WeDoWind Space)

Exclusive digital space

Access to the members-only digital space, which allows all knowledge to be kept in one place for easy access and collaboration, solutions to be easily compared, updated and discussed, democratic decisions to be made and kept transparent, access to the open innovation process even if members miss the workshops (recordings and Jamboard discussions)

Challenges

Access to other challenges on similar relevant topics that are being run in the ecosystem. Access the code, data and knowledge from other challenges, take part in the discussions from other challenges, access the teaching resources from other challenges, contact the people participating in other challenges

2023

How to analyse blade aerodynamics on an operating wind turbine with low-cost pressure sensors?

Julien Deparday, Yuriy Marikovskiy, Tommaso Polonelli, Thomas Clark and Sarah Barber

Wind Energy Science Conference 2023 (WESC203), Glasgow, UK. Zenodo

Aerosense: A Self-Sustainable and Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines

Tommaso Polonelli, Hanna Müller, Weikang Kong, Raphael Fischer, Luca Benini and Michele Magno

IEEE Sensors Journal (Volume: 23, Issue: 1, 01 January 2023)

Extended Taxonomy of Digital Twins

Yuriy Marykovskiy, Imad Abdallah, Sarah Barber and Eleni Chatzi

WESC2023 - Mini Symposia: Digital twins for lifetime assessment of structures

A Graph Neural Network Approach for Aerodynamic Sensor Placement

Gregory Duthé, Imad Abdallah, Sarah Barber and Eleni Chatzi

Simulations and experimental validation of structural damage detection using aerodynamic pressure data

Imad Abdallah, Gregory Duthé, Philip Franz, Szymon Gres, Julien Deparday and Eleni Chatzi

Graph Neural Networks for Aerodynamic Flow Reconstruction from Sparse Sensing

Gregory Duthé, Imad Abdallah, Sarah Barber and Eleni Chatzi

arXiv

2022

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Sarah Barber, Julien Deparday, Yuriy Marykovskiy, Eleni Chatzi, Imad Abdallah, Gregory Duthé, Michele Magno, Tommaso Polonelli, Raphael Fischer and Hanna Müller

Wind Energy Science, Volume 7, issue 4

An experimental system to acquire aeroacoustic properties on wind turbine blades

Julien Deparday, Hanna Müller, Tommaso Polonelli and Sarah Barber

Journal of Physics: Conference Series, Volume 2265, Wind and Wind Farms; Measurement and Testing

Performance Comparison between Decawave DW1000 and DW3000 in low-power double side ranging applications

Tommaso Polonelli, Simon Schläpfer and Michele Magno

2022 IEEE Sensors Applications Symposium (SAS)

Aerosense: Long-Range Bluetooth Wireless Sensor Node for Aerodynamic Monitoring on Wind Turbine Blades

Tommaso Polonelli, Julien Deparday, Hanna Müller, Raphael Fischer, Luca Benini, Sarah Barber and Michele Magno

Journal of Physics: Conference Series, Volume 2265, Wind and Wind Farms; Measurement and Testing

Identifying evolving leading edge erosion by tracking clusters of lift coefficients

Imad Abdallah, Gregory Duthé, Sarah Barber and Eleni Chatzi

Journal of Physics: Conference Series, Volume 2265, Turbine Technology; Artificial Intelligence, Control and Monitoring

Detecting damage via aerodynamic quantities on an aeroelastic structure

Imad Abdallah, Gregory Duthé, Szymon Gres, Julien Deparday, Ronja Fäh, Sarah Barber and Eleni Chatzi

ETH Zurich, Institute of Structural Engineering

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Sarah Barber, Julien Deparday, Yuriy Marykovskiy, Eleni Chatzi, Imad Abdallah, Gregory Duthé, Michele Magno, Tommaso Polonelli, Raphael Fischer and Hanna Müller

Wind Energy Science, vol. 7, no. 4, pp. 1383-1398, Groningen, European Academy of Energy

Using Interpretable Machine Learning for Data-Driven Decision Support for Infrastructure Operation & Maintenance

Eleni Chatzi, Imad Abdallah, Konstantinos Tatsis, S. Osmani and Ignacio Robles

11th International Conference on Bridge Maintenance, Safety and Management (IABMAS 2022), Barcelona, Spain, pp.837-845, Leiden, CRC Press/Balkema

A Physics-Based Reduction with Monitoring Data Assimilation for Adaptive Representations in Structural Systems

Konstantinos Vlachas, Konstantinos Tatsis, Carianne Martinez and Eleni Chatzi

40th IMAC, A Conference and Exposition on Structural Dynamics, Orlando, FL, USA, pp.93-96, Cham: Springer, February 7-10

Hankel matrix-based denoising for statistical damage diagnosis

Szymon Gres, Konstantinos Tatsis, Vasilis K. Dertimanis and Eleni Chatzi

9th International Operational Modal Analysis Conference (IOMAC 2022), Vancouver, Canada Gijón: International Operational Modal Analysis Conference, July 3-6

Optimal Sensor Configuration Design for Virtual Sensing in a Wind Turbine Blade Using Information Theory

Tulay Ercan, Konstantinos Tatsis, Victor Flores Terrazas, Eleni Chatzi and Costas Papadimitriou

In Mao, Z. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series, pp. 67-70, Springer International Publishing

Virtual sensing for SHM: a comparison between Kalman filters and Gaussian processes

E Papatheou, Konstantinos Tatsis, R.S. Battu, Konstantinos Agathos, Marcus Haywood-Alexander, Eleni N. Chatzi, Nikolaos Dervilis and Keith Worden

ISMA2022 conference on Noise and Vibration Engineering, Leuven, Belgium, 12-14 September

Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems: A Tutorial

Konstantinos E. Tatsis, Vasileios K. Dertimanis and Eleni Chatzi

Journal of Structural Dynamics, no. 1, pp. 236-262, Liège: University of Liège

2021

WindNode: A Long-Lasting And Long-Range Bluetooth Wireless Sensor Node for Pressure and Acoustic Monitoring on Wind Turbines

Raphael Fischer, Hanna Müller, Tommaso Polonelli, Luca Benini and Michele Magno

4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)

Ultra-Low Power Wake-Up Receiver for Location Aware Objects Operating with UWB

Tommaso Polonelli, Federico Villani and Michele Magno

2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

Digital Twin Development Framework in the context of Fluid Structure Interaction

Yuriy Marykovskiy, Thomas Clark, Sarah Barber and Eleni Chatzi

ESC2021 "Emerging Technologies and Special Sessions" Digital Twin Technology

Modeling and Monitoring Erosion of the Leading Edge of Wind Turbine Blades

Gregory Duthé, Imad Abdallah, Sarah Barber and Eleni Chatzi

Energies 2021, 14(21), 7262

Learning to diagnose leading edge erosion degradation on an airfoil via aerodynamic pressure coefficients

Gregory Duthé, Imad Abdallah, Yuriy Marykovskiy, Sarah Barber and Eleni Chatzi

Wind Energy Science Conference (WESC 2021), Hannover, 25 – 28 May 2021 (Session Structural Health Monitoring: Applications and Potential in Wind Energy)

Parametric reduced order models for output-only vibration-based crack detection in shell structures

Konstantinos Agathos, Konstantinos E. Tatsis, Konstantinos Vlachas and Eleni Chatzi

Mechanical Systems and Signal Processing, vol. 162, pp. 108051, Amsterdam: Elsevier BV

Conditional variational autoencoders for probabilistic wind turbine blade fatigue estimation using Supervisory, Control, and Data Acquisition data

Charilaos Mylonas, Imad Abdallah and Eleni Chatzi

Wind Energy, vol. 24, no. 10, pp. 1122-1139, Oxford Wiley

Seismic fragility analysis based on artificial ground motions and surrogate modeling of validated structural simulators

Giuseppe Abbiati, Marco Broccardo, Imad Abdallah, Stefano Marelli and Fabrizio Paolacci

Earthquake Engineering & Structural Dynamics, vol. 50 no. 9, pp. 2314-2333, Oxford Wiley

Learning to diagnose leading edge erosion degradation on an airfoil via aerodynamic pressure coefficients

Gregory Duthé, Imad Abdallah, Yuriy Marykovskiy, Sarah Barber and Eleni Chatzi

Geneva, CERN

Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression

Luis David Avendaño Valencia, Imad Abdallah and Eleni Chatzi

Renewable Energy, vol. 170, pp. 539-561, Amsterdam, Elsevier

Modeling and Monitoring Erosion of the Leading Edge of Wind Turbine Blades

Gregory Duthé, Imad Abdallah, Sarah Barber and Eleni Chatzi

Energies, vol. 14: no. 21, pp. 7262, Basel: MDPI

On The Coupling of Reduced Order Modeling with Substructuring of Structural Systems with Component Nonlinearities

Konstantinos Vlachas, Konstantinos E. Tatsis, Konstantinos Agathos, Adam R. Brink, Dane Quinn and Eleni Chatzi

39th Conference and Exposition on Structural Dynamics of the Society for Experimental Mechanics Conference (IMAC XXXIX 2021), Orlando, FL, USA, pp.35-43, Cham: Springer, February 8–11

2020

NB-IoT Versus LoRaWAN: An Experimental Evaluation for Industrial Applications

Massimo Ballerini, Tommaso Polonelli, Davide Brunelli, Michele Magno and Luca Benini

IEEE Transactions on Industrial Informatics (Volume: 16, Issue: 12, December 2020)