Webinar • Big Data: Big Data • Industria y Fabricación

Predicción de fallos en turbinas eólicas con Inteligencia Artificial de GreenByteAgéndalo en tu calendario habitual ¡en tu horario!

Por Dr. Pramod Bangalore,Patrick Strom y Michelle Froese
Jueves, 7 de marzo de 2019, de 11.30 a 12.30 hs Horario de Virginia (US)
Webinar en inglés

Predict, Greenbyte's digital condition monitoring system, uses artificial neural network models that have been rigorously trained to learn from SCADA data and identify impending wind turbine component faults at an early stage.

Predict alerts users of impending failures up to 9 months in advance and can reduce lost production due to forced outage up to 12%.

Dr. Pramod Bangalore, Head of Research at Greenbyte, will walk you through:
 
How the artificial neural networks are trained to crunch SCADA data and achieve 94% accuracy in detecting failures in components
How Predict enables you to act proactively to avoid failures, increase power output and ensure longevity of components
The results of the Predict pilot studies as well as the financial and operational benefits for existing users
Sign up for the webinar and embark on a journey of data science, artificial intelligence and cutting-edge technology!
Agenda
  • 11:30 - 11:50 hs
    Data Scientist & Head of Research por , de Greenbyte
  • 11:50 - 12:10 hs
    Senior Sales Manager por , de Greenbyte
  • 12:10 - 12:30 hs
    Moderator por , de Windpower
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Sponsors
  • Predicción de fallos en turbinas eólicas con Inteligencia Artificial de GreenByte



Ponentes de este webinar
Michelle Froese
Moderator en Windpower
Windpower Engineering & Development
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