
Using Digital Twin Technology to Protect Wind Turbines
Predictive maintenance software and digital twin technology can maximize output and minimize downtime
Digital twins of machines are virtual representations of the real machines live in the cloud and use as their lifeblood data captured from their parts.
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In the heart of Paris, a short walk from the city’s storied opera, GE engineers are busy coding software that will allow them to create “digital twins” of machines. These digital twins are virtual representations of the real machines live in the cloud and use as their lifeblood data captured from their parts.
Using algorithms built on Predix , GE’s software platform for the industrial internet, and a modelling approach developed by Ansys, a leader in engineering simulation software, these engineers use “digital twin technology” to digitally play out different scenarios, such as running an aircraft engine longer and in a hotter or wetter environment. They the use the insights gained from these tests to maximize output and minimize downtime by spotting problems before they lead to an unplanned outage.
This predictive maintenance is not only about using physical sensors on the machines. It is also about using virtual sensors, especially in places where you can’t use a physical sensor. A virtual sensor results from the ability to guess fairly precisely a value (such as temperature or pressure) by using other data from sensors and smart predictive algorithms based on historical data or models.
For instance, GE engineers have developed a digital twin of the Haliade 150-6MW wind turbine’s yaw motors, which enable the 6-megawatt turbine to rotate and position itself into the wind. This digital twin simulates, through virtual sensors, the temperature at various parts of the motors.
To learn more about Digital Twin Technology at GE Renewable Energy,contacting us today.
Read the full story at GE Reports.