An interpretability research of the Xgboost algorithm in remaining useful life prediction

Traditional industrial health management (PHM) and prediction relies on maintenance experience or work mechanism models to acquire the remaining useful life (RUL) of the equipment is becoming increasingly difficult to obtain. In this paper, the data-driven xgboost ensemble learning method is adapted to predict the RUL of aero-engine, the raw data is input into the ensemble learning model after a s...