IM Wind

Development of a sensor-based intelligent monitoring system for wind turbines

WEA Kahrholz

Goals

Monitoring systems help to ensure the cost-effective operation of wind turbines over a service life of 20 years and beyond. This is achieved by predicting and detecting damage, optimizing maintenance and operation, and predicting service life.

As part of the IM WIND project, the measurement setup is planned to be further improved by innovative sensor technology. New data evaluation methods are to be tested and automated, building on the preliminary work in the MISTRALWIND-Projekt. In cooperation with the project partners, a digital twin of the supporting structure of the wind turbine will be created and machine-learning methods will be applied for analysis of the data and results.

In addition, a real-time network infrastructure is being developed, and modules for a variety of monitoring tasks are being deployed.

Contact

IM WIND is lead by the Chair of Non-Destructive testing (ZfP) at the Technical University of Munich (TUM).

For more information about IM WIND please contact  Johannes Rupfle at ZfP.

News

  • TUM ZfP starts new ZIM project on intelligent monitoring systems for wind turbines (3/09/2019)
    Monitoring systems help to ensure the cost-effective operation of wind turbines over a service life of 20 years and beyond. This is achieved by predicting and detecting damage, optimizing maintenance and operation, and predicting service life. But how can these monitoring systems automatically use sensor data? The Chair of non-destructive testing at the Technical University of ...

Project Partners

ASC GmbH
elunic GmbH
Chair of Structural Analysis
clockworkX GmbH

Project Funding

IM Wind is funded by the Bundesministerium für Wirtschaft und Energy (BMWi, German Federal Minsitry for Economic Affairs and Energy).

IM Wind is a “Zentrales Innovationsprogramm Mittelstand” (ZIM) project, which means “Central Innovation Programme for small and medium-sized enterprises (SMEs)”.

  • Project start: 01.09.2019

  • Duration: 30 Months

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