Failure prediction in real time on time series data (wind turbine) can be realized with the use of Open Source. This project will design docs/code that will injest raw sensor data and end up with a real time graph that shows alerts warning that a mechanical failure is imminent.
A data collector will be used to receive raw sensor data and then place the data into a data storage unit. All of the new raw sensor data are associated with the timestamp of when the sensor data was generated, thereby forming what is called a time series. The data collecotr then makes an API call to a web application that puts the new data into a form that enables a training Machine Learning model to make a binary classification (Normal or Not Normal) prediction. A real time series graph is then updated with the prediction, and the graph is pushed to a browser that is connected to the web applicaiton.
Cameron Garrison, Eli Guidera, Troy Nelson, Audrey Reznik, Christina Xu
weekly (thursdays) @ 9am MST
areznik@redhat.com for information regarding this project.