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Home›Operations & Maintenance›TWI Developing Digital Turbine Twins
Operations & Maintenance

March 14, 2017 · about 9 years ago

TWI Developing Digital Turbine Twins

UK-based independent research and technology organisation TWI Ltd has set its sights on harnessing digital twin technology to transform the process of monitoring and maintaining offshore wind turbines.

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UK-based independent research and technology organisation TWI Ltd has set its sights on harnessing digital twin technology to transform the process of monitoring and maintaining offshore wind turbines.

Building on the combined prior expertise gained from previous collaborative projects such as CMSWind, WTBMonitor and TOWERPOWER, TWI is now embarking on a digital twin solution for the wind turbine industry, with the intention of forming a joint project with industrial partners to deliver a fully integrated approach to structural health monitoring for improved reliability of wind turbines.

A condition monitoring system will encompass the entire physical wind turbine providing ongoing structural health analysis.

Simultaneously, this will be mirrored virtually with the creation of a 3D model of the wind turbine in the form of a digital twin, including input from different sensors positioned across the physical entity, to continually feedback monitoring data. The output will be fully comprehensive, real-time assessment of the structural condition of individual wind turbine assets, TWI said.

Tat-Hean Gan, Business Group Manager, Integrity Management at TWI, said that digital twin’s intelligent data processing capability makes it an ideal platform for preventive and predictive maintenance of the wind turbine’s behaviour and condition.

”These virtual models or twins will combine mathematical models describing the physics of the turbine’s operation, with sensor data collected and processed from real assets during real world operations,” Gan said.

“Wind farm operators will benefit from being able to predict structural failure and plan maintenance activities with greater accuracy, affording them more control, resulting in reduced maintenance costs and operational downtime during the wind turbine’s lifespan.”

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