A "ciphered" or transformed version of original sensor data to maintain confidentiality.
Used by students and professionals to build and tune models like Random Forest or XGBoost to predict if a turbine component (like a gearbox or blade) is about to fail. Shinewind_2021-09_to_2022-03_compressed.zip
It typically includes around 40 predictor variables (environmental factors like wind speed, humidity, and temperature) and one target variable indicating the turbine's status or failure risk. A "ciphered" or transformed version of original sensor