3 min Research Talk: Deep Machine Learning for Machine Performance & Damage Prediction
Online Presentations | 04 Feb 2019 | Contributor(s): Elijah Reber
In this talk, we look at how effective a deep neural network is at predicting the failure or energy output of a wind turbine. A data set was obtained that contained sensor data from 17 wind turbines over 13 months, measuring numerous variables, such as spindle speed and blade position and whether...
Deep Machine Learning for Machine Performance and Damage Prediction
Presentation Materials | 08 Aug 2018 | Contributor(s): Elijah Reber, Nickolas D Winovich, Guang Lin
Deep learning has provided opportunities for advancement in many fields. One such opportunity is being able to accurately predict real world events. Ensuring proper motor function and being able to predict energy output is a valuable asset for owners of wind turbines. In this paper, we look at...
Wind Turbine Power Prediction
Tools | 30 Jul 2018 | Contributor(s): Elijah Reber, Nickolas D Winovich, Guang Lin
This tool uses a trained neural network algorithm to predict the energy output and failure of a wind turbine using sensor data
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